• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.1-11
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• 2018

Mapping accurate spatial information is important for constructing three-dimensional (3D) spatial models and managing artificial facilities, and, especially, mapping road centerlines is necessary for constructing accurate road maps. This research developed a semi-automatic methodology for mapping road centerlines using the MMS(Mobile Mapping System) LiDAR(Light Detection And Ranging) point cloud as follows. First, the intensity image was generated from the given MMS LiDAR data through the interpolation method. Next, the line segments were extracted from the intensity image through the edge detection technique. Finally, the road centerline segments were manually selected among the extracted line segments. The statistical results showed that the generated road centerlines had 0.065 m overall accuracy but had some errors in the areas near road signs.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.473-483
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• 2014

Even though the ROC manifold for more than three dimensional space which is an extension of the ROC curve and surface has difficulty to represent graphically, the hypervolume under the ROC manifold (HUM) statistic can be defined and obtained based on AUC and VUS measures for the ROC curve and the ROC surface. Hence the definition and characteristics of the HUM for four dimensional space are studied in this work. By extension of the standard criterion of AUC for probabilities of default based on Basel II, the 13 classes of standard criterion of HUM are proposed in order to discriminate four classification models and some application methods are discussed. In order to explore the standard criterion of HUM whose values are obtained from various distributions, ternary plot is used and explained.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.276-287
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• 2021

Project Management Information System (PMIS) is a special purpose information system that is created to provide useful information for project managers and participants to make effective and efficient decision making during projects. The use of PMIS is increasing in project based industries such as construction, defense, manufacturing, software development, telecommunication, etc. It is generally known that PMIS helps to improve the quality of decision making in project management, and consequently improves the project management performance. However, it is unclear what are the difference of PMIS impacts between industries, and still need to be studied further. The purpose of this study is to compare the impact of PMIS on project management performance between industries. We assume that the effects of PMIS will be different depending on the industry types. Five hypotheses are established and tested by using statistical methods. Data were collected by using a survey questionnaire from those people who had experience of using PMIS in various project related industries such as construction, defense, manufacturing, software development and telecommunication. The survey questionnaire consists of 5 point scale items and were distributed through e-mails and google drive network. A total of 181 responses were collected, and 137 were used for analysis after excluding those responses with missing items. Statistical techniques such as factor analysis and multiple regression are used to analyze the data. Summarizing the results, it is found that the impacts of PMIS quality on the PM performance are different depending on the industry types where PMIS is used. System quality seems to be more important for improving the PM performance in construction industry while information quality seems more important for manufacturing industry. As for the ICT and R&D industries, PMIS seems to have relatively lesser impact compared to construction and manufacturing industries.

• Advances in Computational Design
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• v.5 no.2
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• pp.127-146
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• 2020

Building Information Modeling (BIM) is increasingly used throughout the facility's life cycle for various applications, such as design, construction, facility management, and maintenance. For existing buildings, the geometry of as-built BIM is often constructed using dense, three dimensional (3D) point clouds data obtained with laser scanners. Traditionally, as-built BIM systems do not contain the material and textural information of the buildings' elements. This paper presents a semi-automatic method for generation of material and texture rich as-built BIM. The method captures and integrates material and textural information of building elements into as-built BIM using thermal infrared sensing (TIS). The proposed method uses TIS to capture thermal images of the interior walls of an existing building. These images are then processed to extract the interior walls using a segmentation algorithm. The digital numbers in the resulted images are then transformed into radiance values that represent the emitted thermal infrared radiation. Machine learning techniques are then applied to build a correlation between the radiance values and the material type in each image. The radiance values were used to extract textural information from the images. The extracted textural and material information are then robustly integrated into the as-built BIM providing the data needed for the assessment of building conditions in general including energy efficiency, among others.

• Journal of the Korean Institute of Gas
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• v.4 no.3 s.11
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• pp.39-45
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• 2000

In general, most of the GIS only deal with materials and geometric data which just include position, radius, length of the structure. Therefore it's hard to get corrosion data from it. But the one that an owner of metallic structures want to know is the integrity of the structure. Cathodic Protection System can not protect corrosion on the underground facilities perfectly but protect corrsion effectively. It therefore is necessary to monitor the facilities continually So, we need the development of GIS interconnected a corrosion prediction system on the view point of the efficiency of operation and the protection for a big accident. The results of the development of its system are described in this paper. It can do life prediction and interference analysis and also newest corrosion data should be updated regularly.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.13-20
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• 2022

IEEE 802.11ay Wi-Fi is the next generation wireless technology and operates in mmWave band. It supports the MU-MIMO (Multiple User Multiple Input Multiple Output) transmission in which an AP (Access Point) can transmit multiple data streams simultaneously to multiple STAs (Stations). To this end, the AP should perform MU-MIMO beamforming training with the STAs. For efficient MU-MIMO beamforming training, it is important for the AP to estimate signal strength measured at each STA at which multiple beams are used simultaneously. Therefore, in the paper, we propose a deep learning-based link quality estimation scheme. Our proposed scheme estimates the signal strength with high accuracy by utilizing a deep learning model pre-trained for a certain indoor or outdoor propagation scenario. Specifically, to estimate the signal strength of the multiple concurrent beams, our scheme uses the signal strengths of the respective single beams, which can be obtained without additional signaling overhead, as the input of the deep learning model. For performance evaluation, we utilized a Q-D (Quasi-Deterministic) Channel Realization open source software and extensive channel measurement campaigns were conducted with NIST (National Institute of Standards and Technology) to implement the millimeter wave (mmWave) channel. Our simulation results demonstrate that our proposed scheme outperforms comparison schemes in terms of the accuracy of the signal strength estimation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.4
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• pp.469-476
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• 2009

The new laser scanning technology allows to attain 3D information faster with higher accuracy on surface ground, vegetation and buildings of the earth surface. This acquired information can be used in many areas after modifying them appropriately by users. The contour production for accurate landform is an advanced technology that can reveal the mountain area landscapes hidden by the trees in detail. However, if extremely precise LiDAR data is used in constructing the contour, massive-sized data intricates the contour diagram and could amplify the data size inefficiently. This study illustrates the algorithm producing contour that is filtered in stages for more efficient utilization using the LiDAR contour produced by the detailed landscape data. This filtering stages allow to preserve the original landscape shape and to keep the data size small. Point Filtering determines the produced contour diagram shape and could minimize data size. Thus, in this study we compared experimentally filtered contour with the current digital map(1:5,000).

• Journal of The Korean Astronomical Society
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• v.40 no.3
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• pp.67-82
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• 2007

The basic building block of solar filaments/prominences is thin threads of cool plasma. We have studied the spectral properties of velocity threads, clusters of thinner density threads moving together, by analyzing a sequence of $H{\alpha}$ images of a quiescent filament. The images were taken at Big Bear Solar Observatory with the Lyot filter being successively tuned to wavelengths of -0.6, -0.3, 0.0, +0.3, and +0.6 ${\AA}$ from the centerline. The spectra of contrast constructed from the image data at each spatial point were analyzed using cloud models with a single velocity component, or three velocity components. As a result, we have identified a couple of velocity threads that are characterized by a narrow Doppler width($\Delta\lambda_D=0.27{\AA}$), a moderate value of optical thickness at the $H{\alpha}$ absorption peak($\tau_0=0.3$), and a spatial width(FWHM) of about 1". It has also been inferred that there exist 4-6 velocity threads along the line of sight at each spatial resolution element inside the filament. In about half of the threads, matter moves fast with a line-of-sight speed of $15{\pm}3km\;s^{-1}$, but in the other half it is either at rest or slowly moving with a line-of-sight velocity of $0{\pm}3km\;s^{-1}$. It is found that a statistical balance approximately holds between the numbers of blue-shifted threads and red-shifted threads, and any imbalance between the two numbers is responsible for the non-zero line-of-sight velocity determined using a single-component model fit. Our results support the existence not only of high speed counter-streaming flows, but also of a significant amount of cool matter either being at rest or moving slowly inside the filament.

• Analytical Science and Technology
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• v.7 no.3
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• pp.329-338
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• 1994

The retention behaviors of natural gas components were studied on a single column by gas chromatography. The dead time, $t_0$ was obtained by using extrapolation of homologous series to determine capacity factors. The plots of retention data for homologous series and carbon number at different temperatures were shown to converge into a single point, which point was determined as a dead time. The results of the effect of temperature on the column efficiency for n-butane exhibited the plate number, N incerased with temperature, but the resolution among the fast eluted components decreased. The adsorption enthalpy (${\Delta}H^0{_{ads}}$) for each component on 28% DC 200 stationary phase was determined, and in order to investigate the retention behaviors of natural gas components the regression analysis of log $t_R$, log k' and log ${\alpha}$ vs. van der Waals volume(Vw), molecular connectivity index(X) and hydrophobic fragmental constant(f) were carred out. Good correlation was found between log k' vs. Vw, and log k' vs. f. The correlations between the physical properties of natural gas and the physical parameters were investigated by the linear regression analysis. The relationships between Vw vs. molecular weight and heating value(${\Delta}H_{comb}$), X vs. boiling point, and f vs. molecular weight, boiling point and heating value exhibited the high correlation coefficient more than 0.99. Using the regression equation between the heating value of natural gas and Vw the predicted heating values from $C_6$ to $C_{10}$ showed good agreement with those reported in the literature within 0.2% relative error.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.4
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• pp.331-339
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• 2013

LiDAR has been one of the widely used and important technologies for 3D modeling of ground surface and objects because of its ability to provide dense and accurate range measurement. The objective of this research is to develop a method for automatic detection and modeling of railroad power lines using high density LiDAR data and RANSAC algorithms. For detecting railroad power lines, multi-echoes properties of laser data and shape knowledge of railroad power lines were employed. Cuboid analysis for detecting seed line segments, tracking lines, connecting and labeling are the main processes. For modeling railroad power lines, iterative RANSAC and least square adjustment were carried out to estimate the lines parameters. The validation of the result is very challenging due to the difficulties in determining the actual references on the ground surface. Standard deviations of 8cm and 5cm for x-y and z coordinates, respectively are satisfactory outcomes. In case of completeness, the result of visual inspection shows that all the lines are detected and modeled well as compare with the original point clouds. The overall processes are fully automated and the methods manage any state of railroad wires efficiently.