• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.4
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• pp.347-354
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• 2007

Since large portal service providers started web services for 3D city models around the world using spatial imagery, the competition has been getting intense to provide the models with the higher quality and accuracy. The building models are the most in number among the 3D city model objects, and it takes much time and money to create realistic model due to various shapes and visual appearances of building object. The aforementioned problem is the most significant limitation for the service and the update of the 3D city model of the large area. This study proposed a method of generating realistic 3D building models with quick and economical texture mapping using multiple spatial imagery such as aerial photos or satellite images after reconstructed geometric models of buildings from building layers in digital maps. Based on the experimental results, the suggested method has effectiveness for the generation of the 3D building models using various air-borne imagery and satellite imagery quickly and economically.

• Korea Real Estate Review
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• v.24 no.1
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• pp.7-14
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• 2014

This study, as the temporal and spatial data for the real price apartment in Seoul from January 2006 to June 2013, empirically compared and analyzed the estimation result of apartment price using OLS by hedonic price model for the problem of space-time correlation, temporal autoregressive model (TAR) considering temporal effect, spatial autoregressive model (SAR) spatial effect and spatiotemporal autoregressive model (STAR) spatiotemporal effect. As a result, the adjusted R-square of STAR model was increased by 10% compared that of OLS model while the root mean squares error (RMSE) was decreased by 18%. Considering temporal and spatial effect, it is observed that the estimation of apartment price is more correct than the existing model. As the result of analyzing STAR model, the apartment price is affected as follows; area for apartment(-), years of apartment(-), dummy of low-rise(-), individual heating (-), city gas(-), dummy of reconstruction(+), stairs(+), size of complex(+). The results of other analysis method were the same. When estimating the price of real estate using STAR model, the government officials can improve policy efficiency and make reasonable investment based on the objective information by grasping trend of real estate market accurately.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.83-95
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• 2019

Recently, a variety of IoT data is collected by attaching geosensors to many vehicles that are on the road. IoT data basically has time and space information and is composed of various data such as temperature, humidity, fine dust, Co2, etc. Although a certain sensor data can be retrieved using time, latitude and longitude, which are keys to the IoT data, advanced search engines for IoT data to handle high-level user queries are still limited. There is also a problem with searching large amounts of IoT data without generating indexes, which wastes a great deal of time through sequential scans. In this paper, we propose a unified spatial index model that handles both grid and trajectory queries using a cell-based space-filling curve method. also it presents a visualization method that helps user grasp intuitively. The Trajectory query is to aggregate the traffic of the trajectory cells passed by taxi on the road searched by the user. The grid query is to find the cells on the road searched by the user and to aggregate the fine dust. Based on the generated spatial index, the user interface quickly summarizes the trajectory and grid queries for specific road and all roads, and proposes a Web-based prototype system that can be analyzed intuitively through road and heat map visualization.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.376-386
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• 2020

The aim of this study was to develop a new efficient strategy that uses the Vector form Intrinsic Finite-element (VFIFE) method to conduct the static and dynamic analyses of marine pipes. Nonlinear problems, such as large displacement, small strain, and contact and collision, can be analyzed using a unified calculation process in the VFIFE method according to the fundamental theories of point value description, path element, and reverse motion. This method enables analysis without the need to integrate the stiffness matrix of the structure, because only motion equations of particles established according to Newton's second law are required. These characteristics of the VFIFE facilitate the modeling and computation efficiencies in analyzing the nonlinear dynamic problem of flexible pipe with large deflections. In this study, a three-dimensional (3-D) dynamical model based on 3-D beam element was established according to the VFIFE method. The deep-sea flexible pipe was described by a set of spatial mass particles linked by 3-D beam element. The motion and configuration of the pipe are determined by these spatial particles. Based on this model, a simulation procedure to predict the 3-D dynamical behavior of flexible pipe was developed and verified. It was found that the spatial configuration and static internal force of the mining pipe can be obtained by calculating the stationary state of pipe motion. Using this simulation procedure, an analysis was conducted on the static and dynamic behaviors of the flexible mining pipe based on a 1000-m sea trial system. The results of the analysis proved that the VFIFE method can be efficiently applied to the static and dynamic analyses of marine pipes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3172-3193
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• 2022

Cognitive radio-simultaneous wireless information and power transfer (CR-SWIPT) has attracted much interest since it can improve both the spectrum and energy efficiency of wireless networks. This paper focuses on the resource sharing between a point-to-point primary system (PRS) and a multiuser multi-antenna cellular cognitive radio system (CRS) containing a large number of cognitive users (CUs). The resource sharing optimization problem is formulated by jointly scheduling CUs and adjusting the transmit power at the cognitive base station (CBS). The effect of accessing CUs' spatial channel correlation on the possible transmit power of the CBS is investigated. Accordingly, we provide a low-complexity suboptimal approach termed the semi-correlated semi-orthogonal user selection (SC-SOUS) algorithm to enhance the spectrum efficiency. In the proposed algorithm, CUs that are highly correlated to the information decoding primary receiver (IPR) and mutually near orthogonal are selected for simultaneous transmission to reduce the interference to the IPR and increase the sum rate of the CRS. We further develop a spatial correlation-based resource sharing (SC-RS) strategy to improve energy sharing performance. CUs nearly orthogonal to the energy harvesting primary receiver (EPR) are chosen as candidates for user selection. Therefore, the EPR can harvest more energy from the CBS so that the energy utilization of the network can improve. Besides, zero-forcing precoding and power control are adopted to eliminate interference within the CRS and meet the transmit power constraints. Simulation results and analysis show that, compared with the existing CU selection methods, the proposed low-complex strategy can enhance both the achievable sum rate of the CRS and the energy sharing capability of the network.

• Current Optics and Photonics
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• v.5 no.4
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• pp.431-443
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• 2021

Sparse unmixing has been proven to be an effective method for hyperspectral unmixing. Hyperspectral images contain rich spectral and spatial information. The means to make full use of spectral information, spatial information, and enhanced sparsity constraints are the main research directions to improve the accuracy of sparse unmixing. However, many algorithms only focus on one or two of these factors, because it is difficult to construct an unmixing model that considers all three factors. To address this issue, a novel algorithm called multiview-based spectral weighted and low-rank row-sparsity unmixing is proposed. A multiview data set is generated through spectral partitioning, and then spectral weighting is imposed on it to exploit the abundant spectral information. The row-sparsity approach, which controls the sparsity by the l_2,0 norm, outperforms the single-sparsity approach in many scenarios. Many algorithms use convex relaxation methods to solve the l_2,0 norm to avoid the NP-hard problem, but this will reduce sparsity and unmixing accuracy. In this paper, a row-hard-threshold function is introduced to solve the l_2,0 norm directly, which guarantees the sparsity of the results. The high spatial correlation of hyperspectral images is associated with low column rank; therefore, the low-rank constraint is adopted to utilize spatial information. Experiments with simulated and real data prove that the proposed algorithm can obtain better unmixing results.

• 한국전산유체공학회:학술대회논문집
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• 2009.11a
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• pp.228-230
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• 2009

The moment-of-fluid (MOF) method is a new volume-tracking method that accurately treats evolving material interfaces. Based on the moment data (volume and centroid) for each material, the material interfaces are reconstructed with second-order spatial accuracy in a strictly conservative manner. The MOF method is coupled with a stabilized finite element incompressible Navier-Stokes solver for two fluids, namely water and air. The effectiveness of the MOF method is demonstrated with a free-surface dam-break problem.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.12-15
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• 1996

The purpose of image sequence coding is to reduce the spatio-temporal redundancies. The transform coding such as DCT is used for the spatial redundancies. In this paper, the optical flow method is applied to solve the problem of temporal redundancies. So far, pixel intensity conservation has been used to solve the optical flow. We used the neighborhood information as well as pixel intensity conservation. And we compared the merits and demerits of the conventional method and the proposed method in this paper.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.103-105
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• 2009

This paper presents a pseudorandom tag arrangement for improved RFID based mobile robot localization. First, four repetitive tag arrangements, including square, parallelogram, tilted square, and equilateral triangle, are examined. For each tag arrangement, the difficulty in tag installation and the problem of tag invisibility are discussed. Then, taking into account both tag invisibility and tag installation, a pseudorandom tag arrangement is proposed, which is inspired from a Sudoku puzzle. It is shown that the proposed tag arrangement exhibits spatial randomness quite successively without increased difficulty in installation.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.749-750
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• 2008

It is often required to display 3-D data onto a 2-D screen and to examine and verify validity of data. LIDAR data is a good example. They represent 3-D spatial information in text format. However, it is very difficult to examine data on a 2-D screen. A 3-D data viewing system has been implemented and tested in order to solve the problem.