• Journal of Information Processing Systems
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• v.16 no.2
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• pp.406-420
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• 2020

In order to make up the deficiencies of the existing research results which cannot effectively deal with the nearest neighbor query based on the line segments in obstacle space, the k nearest neighbor query method of line segment in obstacle space is proposed and the STA_OLkNN algorithm under the circumstance of static obstacle data set is put forward. The query process is divided into two stages, including the filtering process and refining process. In the filtration process, according to the properties of the line segment Voronoi diagram, the corresponding pruning rules are proposed and the filtering algorithm is presented. In the refining process, according to the relationship of the position between the line segments, the corresponding distance expression method is put forward and the final result is obtained by comparing the distance. Theoretical research and experimental results show that the proposed algorithm can effectively deal with the problem of k nearest neighbor query of the line segment in the obstacle environment.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.2 s.32
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• pp.51-63
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• 2005

With the emerging mobile technologies, applications based on GIS are also getting more attention recently. But it is known to have some limitations in being served in different types of mobile devices and platforms. While information services are limited by data format and data exchange between platforms, the eXtensible Markup Language(XML) is getting focused as the most promising technology as the solution to such problems. Geographic Markup Language(GML) is based on XML technology and is being frequently mentioned recently as the solution to service problem on different mobile devices as well as the internet. In this study, we suggested the framework to use the GML in order to transfer and represent geographical data through the on-line or wireless platforms. We compared different application types which are currently used with GML and proposed to improve GIS services using the GML in geographical data transfer and description.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.2 s.36
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• pp.23-32
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• 2006

This study shows that new methodology improved the problem of unaided eye test level with the digital orthophoto technique can survey more objectively and efficiently any cadastral non-coincidence than existing prior methodologies. For applying to it, we explore eligible other methodologies, and then build up the application strategy of them. New prototype system is implemented with it. Also, we say the availability of new methodology by applying to study area. As a result, we suggest cadastral non-coincidence surveying method based on point-correspondence more objective and more efficient. As a result of comparing with old method and new on same study area for making adequacy, they hardly ever has the difference of accuracy. Constantly, cadastral non-coincidence surveying method based on point-correspondence is acceptable way on the cadastral survey.

• Journal of Korean Society for Geospatial Information Science
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• v.6 no.1 s.11
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• pp.105-116
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• 1998

The spreading of hot waste water discharged from the coastal power station is a new problem to marin e circumstances and the fishery. Because the survey of hot waste water discharges should be performed is multaneously across wide areas, it is very difficult. Some sensors of the Landsat can draw the spread and distribution of water temperature from wavelength range of thermal infrared. The present study applied the GIS after stretching DN for the purpose of drawing a more accurate distribution of water temperature. Accordingly, the pattern of water temperature distribution could be expressed more precisely for a broad area, and the spread and distribution of hot waste water could be analyzed economically.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.244-250
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• 2003

In this paper, the relationship between a slave robot and the uncertain remote environment is modeled as the impedance to generate the virtual force to feed back to the operator. For the control of a tele-operated mobile robot equipped with camera, the tele-operated mobile robot take pictures of remote environment and sends the visual information back to the operator over the Internet. Because of the limitation of communication bandwidth and narrow view-angles of camera, it is not possible to watch the environment clearly, especially shadow and curved areas. To overcome this problem, the virtual force is generated according to both the distance between the obstacle and robot and the approaching velocity of the obstacle. This virtual force is transferred back to the master over the Internet and the master(two degrees of freedom joystick), which can generate force, enables a human operator to estimate the position of obstacle in the remote environment. By holding this master, in spite of limited visual information, the operator can feel the spatial sense against the remote environment. This force reflection improves the performance of a tele-operated mobile robot significantly.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.131-143
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• 2012

This paper introduces the double-density discrete wavelet transform using 3 direction separable processing method, which is a discrete wavelet transform that combines the double-density discrete wavelet transform and quincunx sampling method, each of which has its own characteristics and advantages. The double-density discrete wavelet transform is nearly shift-invariant. But there is room for improvement because not all of the wavelets are directional. That is, although the double-density DWT utilizes more wavelets, some lack a dominant spatial orientation, which prevents them from being able to isolate those directions. The dual-tree discrete wavelet transform has a more computationally efficient approach to shift invariance. Also, the dual-tree discrete wavelet transform gives much better directional selectivity when filtering multidimensional signals. But this transformation has more cost complexity Because it needs eight digital filters. Therefor, we need to hybrid transform which has the more directional selection and the lower cost complexity. A solution to this problem is a the double-density discrete wavelet transform using 3 direction separable processing method. The proposed wavelet transformation services good performance in image and video processing fields.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.7
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• pp.1-11
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• 2006

Through the analysis of conventional TVD limiters, a new multi-dimensional limiting function is derived for an oscillation control in multi-dimensional flows. Then, Multi-dimensional Limiting Process (MLP) is developed with the multi-dimensional limiting function. The major advantage of MLP is to prevent oscillations across a multi-dimensional discontinuity, and it is readily compatible with more than 3rd order spatial interpolation. Moreover, MLP shows a good convergence characteristic in a steady problem and it is very simple to be implemented. Through numerical test cases, it is verified that MLP substantially improves accuracy, efficiency and robustness both in continuous and discontinuous flows.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.272-287
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• 2017

This paper proposes new methods, named Derivative Code (DerivativeCode) and Derivative Code Pattern (DCP), for object recognition. The discriminative derivative code is used to capture the local relationship in the input image by concatenating binary results of the mathematical derivative value. Gabor based DerivativeCode is directly used to solve the palmprint recognition problem, which achieves a much better performance than the state-of-art results on the PolyU palmprint database. A new local pattern method, named Derivative Code Pattern (DCP), is further introduced to calculate the local pattern feature based on Dervativecode for object recognition. Similar to local binary pattern (LBP), DCP can be further combined with Gabor features and modeled by spatial histogram. To evaluate the performance of DCP and Gabor-DCP, we test them on the FERET and PolyU infrared face databases, and experimental results show that the proposed method achieves a better result than LBP and some state-of-the-arts.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.4
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• pp.383-390
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• 2016

Remote sensing data has been widely used in the estimation of crop yields by employing statistical methods such as regression model. Machine learning, which is an efficient empirical method for classification and prediction, is another approach to crop yield estimation. This paper described the corn yield estimation in Iowa State using four machine learning approaches such as SVM (Support Vector Machine), RF (Random Forest), ERT (Extremely Randomized Trees) and DL (Deep Learning). Also, comparisons of the validation statistics among them were presented. To examine the seasonal sensitivities of the corn yields, three period groups were set up: (1) MJJAS (May to September), (2) JA (July and August) and (3) OC (optimal combination of month). In overall, the DL method showed the highest accuracies in terms of the correlation coefficient for the three period groups. The accuracies were relatively favorable in the OC group, which indicates the optimal combination of month can be significant in statistical modeling of crop yields. The differences between our predictions and USDA (United States Department of Agriculture) statistics were about 6-8 %, which shows the machine learning approaches can be a viable option for crop yield modeling. In particular, the DL showed more stable results by overcoming the overfitting problem of generic machine learning methods.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.454-458
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• 2007

Nonpoint source (NPS) pollution is a serious problem causing the degradation of soil and water quality. Concentrated overland flow is the primary transport mechanism for a large amount of NPS pollutants from hillslope areas to downslope areas in a watershed. In this study, a soil erosion model, nLS model, to identify transitional overland flow regions (i.e., ephemeral gully head areas) was developed using the kinematic wave overland flow theory. Spatial data, including digital elevation models (DEMs), soil, and landcover, were used in the GIS-based model algorithm. The model was calibrated and validated using gully head locations in a large agricultural watershed, which were identified using 1-m aerial photography. The model performance was better than two previous approaches; the overall accuracy of the nLS model was 72 % to 87 % in one calibration subwatershed and the mean overall accuracy was 75 to 89 % in four validation subwatersheds, showing that the model well predicted potential transitional erosion areas at different watersheds. However, the user accuracy in calibration and validation was still low. To improve the user accuracy and study the effects of DEM resolution, finer resolution DEMs may be preferred because DEM grid is strongly sensitive to estimating model parameters. Information gained from this study can improve assessing soil erosion process due to concentrated overland flow as well as analyze the effect of microtopographic landscapes, such as riparian buffer areas, in NPS control.