• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10C
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• pp.990-999
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• 2007

In this paper, we propose the region-based image retrieval method using JSEG which is a method for unsupervised segmentation of color-texture regions. JSEG is an algorithm that discretizes an image by color classification, makes the J-image by applying a region to window mask, and then segments the image by using a region growing and merging. The segmented image from JSEG is given to a user as the query image, and a user can select a few segmented regions as the query region. After finding the MBR of regions selected by user query and generating the multiple window masks based on the center point of MBR, we extract the feature vectors from selected regions. We use the accumulated histogram as the global descriptor for performance comparison of extracted feature vectors in each method. Our approach fast and accurately supplies the relevant images for the given query, as the feature vectors extracted from specific regions and global regions are simultaneously applied to image retrieval. Experimental evidence suggests that our algorithm outperforms the recent image-based methods for image indexing and retrieval.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.61-69
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• 2014

Collaborative filtering recommendation creates similar item subset or similar user subset based on user preference about items and predict user preference to particular item by using them. Thus, if preference matrix has low density, reliability of recommendation will be sharply decreased. To solve these problems we suggest Hybrid Preference Prediction Technique Using Weighting based Data Reliability. Preference prediction is carried out by creating similar item subset and similar user subset and predicting user preference by each subset and merging each predictive value by weighting point applying model condition. According to this technique, we can increase accuracy of user preference prediction and implement recommendation system which can provide highly reliable recommendation when density of preference matrix is low. Efficiency of this system is verified by Mean Absolute Error. Proposed technique shows average 21.7% improvement than Hao Ji's technique when preference matrix sparsity is more than 84% through experiment.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.123-132
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• 2019

This study is to estimate the spatial soil moisture using Terra MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data and machine learning technique. Using the 3 years (2015~2017) data of MODIS 16 days composite NDVI (Normalized Difference Vegetation Index) and daily Land Surface Temperature (LST), ground measured precipitation and sunshine hour of KMA (Korea Meteorological Administration), the RDA (Rural Development Administration) 10 cm~30 cm average TDR (Time Domain Reflectometry) measured soil moisture at 78 locations was tested. For daily analysis, the missing values of MODIS LST by clouds were interpolated by conditional merging method using KMA surface temperature observation data, and the 16 days NDVI was linearly interpolated to 1 day interval. By applying the RNN-LSTM (Recurrent Neural Network-Long Short Term Memory) artificial neural network model, 70% of the total period was trained and the rest 30% period was verified. The results showed that the coefficient of determination ($R^2$), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency were 0.78, 2.76%, and 0.75 respectively. In average, the clay soil moisture was estimated well comparing with the other soil types of silt, loam, and sand. This is because the clay has the intrinsic physical property for having narrow range of soil moisture variation between field capacity and wilting point.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.49-62
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• 2022

Borehole Data is geotechnical information provided so that workers can safely perform construction at the field. It creates 3D data and supports viewing as a 3D image. Currently, all Korean companies that develop programs using 3D visualization use the MVS program developed by C Tech Development Corporation. However, the MVS program is a commercial program, and it is difficult to use MVS in 3D related programs developed by Korean Companies. In this paper, we propose to develop a program that can replace MVS to generate a 3D stratum model from clustered borehole information using Python's Gempy open-source. The 3D stratum model program can creates point data for each stratum and can creates a surface for each stratum through interpolation. Then, the 3D stratum model program is completed by merging the surfaces of each stratum. It was confirmed that there was no difference when a 3D model was created and compared with the MVS program and the proposed program from the borehole data of a Goyang area.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.95-101
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• 2023

Colmap is one of the innovative artificial intelligence technologies, highly effective as a tool in 3D reconstruction tasks. Moreover, it excels at constructing intricate 3D models by utilizing images and corresponding metadata. Colmap generates 3D models by merging 2D images, camera position data, depth information, and so on. Through this, it achieves detailed and precise 3D reconstructions, inclusive of objects from the real world. Additionally, Colmap provides rapid processing by leveraging GPUs, allowing for efficient operation even within large data sets. In this paper, we have presented a method of collecting 2D images of traditional Korean towers and reconstructing them into 3D models using Colmap. This study applied this technology in the restoration process of traditional stone towers in South Korea. As a result, we confirmed the potential applicability of Colmap in the field of cultural heritage restoration.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.551-566
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• 2016

In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. The degradation results in noise and blurring which badly affect identification and extraction of useful information in image data. Especially, the degradation gives bad influence in the analysis of images collected over the scene with complicate surface structure such as urban area. This study proposes a multi-stage image restoration to improve the accuracy of detailed analysis for the images collected over the complicate scene. The proposed method assumes a Gaussian additive noise, Markov random field of spatial continuity, and blurring proportional to the distance between the pixels. Point-Jacobian Iteration Maximum A Posteriori (PJI-MAP) estimation is employed to restore a degraded image. The multi-stage process includes the image segmentation performing region merging after pixel-linking. A dissimilarity coefficient combining homogeneity and contrast is proposed for image segmentation. In this study, the proposed method was quantitatively evaluated using simulation data and was also applied to the two panchromatic images of super-high resolution: Dubaisat-2 data of 1m resolution from LA, USA and KOMPSAT3 data of 0.7 m resolution from Daejeon in the Korean peninsula. The experimental results imply that it can improve analytical accuracy in the application of remote sensing high resolution panchromatic imagery.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.8
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• pp.86-96
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• 2000

The representative area among the ones whose cost increases as the integration ratio increases is the test area. As the relative cost of hardware decreases, the BIST method has been focued on as the future-oriented test method. The biggest drawback of it is the increasing test time to obtain the acceptable fault coverage. This paper proposed a BIST implementation method to reduce the test times. This method uses an input grouping and test point insertion method, in which the definition of test point is different from the previous one. That is, the test points are defined on the basis of the internal nodes which are the reference points of the input grouping and are merging points of the grouped signals. The main algorithms in the proposed method were implemented with C-language, and various circuits were used to apply the proposed method for experiment. The results showed that the test time could be reduced to at most $1/2^{40}$ of the pseudo-random pattern case and the fault coverage were also increased compared with the conventional BIST method. The relative hardware overhead of the proposed method to the circuit under test decreases as th e size of the circuit to be tested increases, and the delay overhead by the BIST utility is negligible compared to that of the original circuit. That means, the proposed method can be applied efficiently to large VLSI circuits.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.4
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• pp.105-112
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• 2018

This study aims to apply 3D scanning technology to the field of landscape planning design. Through this, 3D scans were conducted on Soswaewon Garden and Seongrakwon Gardens to find directions for traditional landscape planning and designs. The results as follows. First, the actual measurement of the traditional garden through a 3D scan confirmed that a precise three-dimensional modeling of ${\pm}3-5mm$ error was constructed through the merging of coordinate values based on point data acquired at each observation point and postprocessing. Second, as a result of the 3D survey, the Soswaewon Garden obtained survey data on Jewoldang House, Gwangpunggak Pavilion, the surrounding wall, stone axis, and Aeyangdan wall, while the Seongnakwon Garden obtained survey data on the topography, rocks and waterways around the Yeongbyeokji pond area. The above data have the advantage of being able to monitor the changing appearance of the garden. Third, spatial information developed through 3D scans could be developed with a three-dimensional drawing preparation and inspection tool that included precise real-world data, and this process ensured the economic feasibility of time and manpower in the actual survey and investigation of landscaping space. In addition, modelling with a three-dimensional 1:1 scale is expected to be highly efficient in that reliable spatial data can be maintained and reprocessed to a specific size depending on the size of the design. In addition, from a long-term perspective, the deployment of 3D scan data is easy to predict and simulate changes in traditional landscaping space over time.

• Journal of Digital Contents Society
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• v.16 no.4
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• pp.659-669
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• 2015

Recently, media art is transforming from analogue to 'digital', and from 2D to '3D'. In particular, the range of utilizing 3D Media Art is getting wider through merging with other genres of contents in the digital environments, such as Media façade, Hologram, Virtual reality, App application, and etc. Therefore, by referring to the 3D award-winning works of Pirx Ars Electronica, which are regarded as the most outstanding works of media art of today, factors that affect sensation of visual immersion have been analyzed, through which strategies for maximizing viewers' interests in media arts and heightening their emotions while viewing have been determined. Based on the findings of the study, it has been shown that such works of media arts that involve development of concepts with 'creativity' and 'variability' from the perspective of visual concept, such as 3D modeling and mapping, with 'consistency' through out all concepts, as well as the works with stronger 'restriction' of concept within its animation and postproduction, attracted more interests from the viewer. From the point of view with visual four steps in composition, positioning the change in quality of 3D 'shape' and 'material' following the four-step rule, and gradual increase of change in quantity within the 'number' and 'size', in addition to increased degree of systematization within the change in editing, such as the 'scene change', resulted in more heightened emotions from the viewer. Thus, in order to maximize sensation of visual immersion, strategies for 'developing 3D visual concepts' while 'synchronizing' them, as well as 'strengthening the four steps within 3D visual composition' while 'systematizing' them should be emphasized.

• Journal of the Economic Geographical Society of Korea
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• v.18 no.3
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• pp.267-280
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• 2015

The European civil aviation industry, which had lower technical skills, capital strength and market scale than the U.S., adopted the production system of joint development and division labor between the nations of Europe. Each plant locations strengthened their specialization of the production branch in the past 40 years with a geographical accumulation of the specialized manufacturing facilities, suppliers, universities and laboratories by the logic of geographical proximity and learning effect. The cargo plane transportation system in the production of short- and medium-haul aircraft facilitated the geographical dispersion of manufacturing process and the logistical linkage among the various plant locations. But the production of long-haul large aircraft(A380) chosen the transportation system by the cargo ship because of the size and weight. Considering the transportation system by the cargo ship, the choice of Toulouse as a final assembly plant location was the irrational locational decision from a locational point of view. This locational choice is explained by the merging process of the European civil aviation industry, the logic of learning effect and geographical proximity, and the active attraction support policy.