• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.16-41
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• 2020

Geospatial input setting to represent the reality of spatial distribution or quantitative property within model has become a major interest in earth system simulation. Many studies showed the variation of grid resolution could lead to drastic changes of spatial model results because of insufficient surface property estimations. Hence, in this paper, the authors proposed Monte Carlo Integration (MCI) to apply spatial probability (SP) in a spatial-sampling framework using a three-dimensional point cloud (3DPC) to keep the optimized spatial distribution and area/volume property of buildings in urban area. Three different decision rule based building identification results were compared : SP threshold, cell size, and 3DPC density. Results shows the identified building area property tend to increase according to the spatial sampling grid area enlargement. Hence, areal building property manipulation in the sampling frameworks by using decision rules is strongly recommended to increase reliability of geospatial modeling and analysis results. Proposed method will support the modeling needs to keep quantitative building properties in both finer and coarser grids.

• Elastomers and Composites
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• v.37 no.4
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• pp.211-216
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• 2002

The polymer-polymer interaction parameter, x 23t, of the styrene-butadiene polymer (SBR) and ethylene-propylene-diene terpolymer (EPDM) was investigated by observing the phase behavior of the ternary system of SBR/EPDM/solvent. The solvent used in this study was benzene acting as a good solvent for SBR but as a poor solvent for EPDM. Ternary solutions with various concentrations and mixing ratios of the two component polymers were separated into two phases by temperature change The cloud point curves (CPC) showed that the differerence of solvent affinities toward each polymer and the repulsive interaction between two polymers considerably affect the shape of CPC near 15℃. In the temperature range of 5℃ ~ 25℃, incompatible behaviours arised from both the difference of mixing ratios and concentration were clearly observed. Also the phase separation temperature greatly influenced on the composition of each separated phase. The calculated x 23t values from Flory-Huggins theory were in the range of 0.6301 ~ 1.0775, which suggest that the SBR/EPDM systems are incompatible.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.6
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• pp.88-94
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• 2024

This study introduces a technique for generating parametric BIM models of retaining walls using point cloud data (PCD). Efficient maintenance requires reflecting the current representation of retaining walls, accounting for any discrepancies between the as-built structure and initial drawing. For this, a RANSAC-based algorithm was employed to extract the height and path coordinates from acquired and refined PCD. BIM models were then automatically generated by defining sectional parameters. Applied to a real retaining wall, the algorithm demonstrated a maximum height extraction error of 1.77% and a path coordinate extraction error of 0.88%. This method offers a way to automatically generate BIM models, even when basic data is limited, and there is a the potential to enhance the efficiency of retaining wall maintenance.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.345-352
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• 2022

Recent LiDAR(Light Detection And Ranging) sensor is used for scanning object around in real-time. This sensor can detect movement of the object and how it has changed. As the production cost of the sensors has been decreased, LiDAR begins to be used for various industries such as facility guard, smart city and self-driving car. However, LiDAR has a large input data size due to its real-time scanning process. So another way for processing a large amount of data are needed in LiDAR system because it can cause a bottleneck. This paper proposes edge computing to compress massive point cloud for processing quickly. Since laser's reflection range of LiDAR sensor is limited, multiple LiDAR should be used to scan a large area. In this reason multiple LiDAR sensor's data should be processed at once to detect or recognize object in real-time. Edge computer compress point cloud efficiently to accelerate data processing and decompress every data in the main cloud in real-time. In this way user can control LiDAR sensor in the main system without any bottleneck. The system we suggest solves the bottleneck which was problem on the cloud based method by applying edge computing service.

• International journal of advanced smart convergence
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• v.1 no.2
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• pp.12-15
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• 2012

Energy costs for operating and cooling computing resources in Cloud infrastructure have increased significantly up to the point where they would surpass the hardware purchasing costs. Thus, reducing the energy consumption can save a significant amount of management cost. One of major approach is removing hardware over-provisioning. In this paper, we propose a technique that facilitates power saving through reducing resource over provisioning based on virtualization technology. To this end, we use dynamic workload shaping to reschedule and redistribute job requests considering overall power consumption. In this paper, we present our approach to shape workloads dynamically and distribute them on virtual machines and physical machines through virtualization technology. We generated synthetic workload data and evaluated it in simulating and real implementation. Our simulated results demonstrate our approach outperforms to when not using no workload shaping methodology.

• Journal of the Korean Society of Safety
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• v.10 no.2
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• pp.97-104
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• 1995

To evaluate readily the effect of unconfined vapor cloud explosion(UVCE) having high possibility of accident and risk in chemical industries, the expert system of UVCE was developed and its applicability on a real accident was analyzed. We found that the hazard of UVCE could be well evaluated from the TNT equivalency model and the empirical loss data produced by overpressure for chemical facilities. By using the developed expert system, the size of vapor cloud, the quantity of vaporization, the released energy, the overpressure range from explosion point, and the impact damage of each installation could be estimated respectively. Also, probable maximum loss and catastrophic loss potential for real accident( cyclohexane release in Flixborough Nypro company) were estimated and compared with damages of the accident. As a result, the developed expert system could be well applicable to real accident.

• Tunnel and Underground Space
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• v.19 no.1
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• pp.1-10
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• 2009

Site characterization for structural stability in rock masses mainly involves the collection of joint property data, and in the current practice, much of this data is collected by hand directly at exposed slopes and outcrops. There are many issues with the collection of this data in the field, including issues of safety, slope access, field time, lack of data quantity, reusability of data and human bias. It is shown that information on joint orientation, spacing and roughness in rock masses, can be automatically extracted from LIDAR (light detection and ranging) point floods using the currently available Split-FX point cloud processing software, thereby reducing processing time, safety and human bias issues.

• Publications of The Korean Astronomical Society
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• v.27 no.4
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• pp.165-169
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• 2012

We observed an area of 10 $deg^2$ of the Large Magellanic Cloud using the Infrared Camera (IRC) onboard AKARI. The observations were carried out using five imaging filters (3, 7, 11, 15, and $24{\mu}m$) and the prism disperser ($2-5{\mu}m$, ${\lambda}/{\Delta}{\lambda}{\sim}20$) equipped in the IRC. This paper presents an outline of the survey project and also describes very briefly the newly compiled near- to mid-infrared point source catalog. The $10{\sigma}$ limiting magnitudes are 17.9, 13.8, 12.4, 9.9, and 8.6 mag at 3.2, 7, 11, 15 and $24{\mu}m$, respectively. The photometric accuracy is estimated to be about 0.1 mag at $3.2{\mu}m$ and 0.06 - 0.07 mag in the other bands. The position accuracy is 0.3" at 3.2, 7 and $11{\mu}m$ and 1.0" at 15 and $24{\mu}m$. The sensitivities at 3.2, 7, and $24{\mu}m$ are roughly comparable to those of the Spitzer SAGE LMC point source catalog, while the AKARI catalog provides the data at 11 and $15{\mu}m$, covering the near- to mid-infrared spectral range continuously.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.133-138
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• 2016

This paper describes the track initiation and target-tracking filter for ship tracking in a marine environment by using Light Detection And Ranging (LiDAR). LiDAR with three-dimensional scanning capability is more useful for target tracking in the short to medium range compared to RADAR. LiDAR has rotating multi-beams that return point clouds reflected from targets. Through preprocessing the cluster of the point cloud, the center point can be obtained from the cloud. Target tracking is carried out by using the center points of targets. The track of the target is initiated by investigating the normalized distance between the center points and connecting the points. The regular track obtained from the track initiation can be maintained by the target-tracking filter, which is commonly used in radar target tracking. The target-tracking filter is constructed to track a maneuvering target in a cluttered environment. The target-tracking algorithm including track initiation is experimentally evaluated in a sea-trial test with several boats.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3
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• pp.452-458
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• 2013

Over the past several years, many studies have been carried out in the field of 3D data inspection systems. Several attempts have been made to improve the quality of manufactured parts. The introduction of laser sensors for inspection has made it possible to acquire data at a remarkably high speed. In this paper, a robust inspection technique for detecting defects in 3D pressed parts using laser-scanned data is proposed. Point cloud data are segmented for the extraction of features. These segmented features are used for shape matching during the localization process. An iterative closest point (ICP) algorithm is used for the localization of the scanned model and CAD model. To achieve a higher accuracy rate, the ICP algorithm is modified and then used for matching. To enhance the speed of the matching process, aKd-tree algorithm is used. Then, the deviation of the scanned points from the CAD model is computed.