• Journal of Information Processing Systems
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• v.9 no.1
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• pp.1-30
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• 2013

The capitalization of know-how, knowledge management, and the control of the constantly growing information mass has become the new strategic challenge for organizations that aim to capture the entire wealth of knowledge (tacit and explicit). Thus, knowledge mapping is a means of (cognitive) navigation to access the resources of the strategic heritage knowledge of an organization. In this paper, we present a new mapping approach based on the Boolean modeling of critical domain knowledge and on the use of different data sources via the data mining technique in order to improve the process of acquiring knowledge explicitly. To evaluate our approach, we have initiated a process of mapping that is guided by machine learning that is artificially operated in the following two stages: data mining and automatic mapping. Data mining is be initially run from an induction of Boolean case studies (explicit). The mapping rules are then used to automatically improve the Boolean model of the mapping of critical knowledge.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.1 s.31
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• pp.45-53
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• 2005

Korea is formed a mountainous district at 70% of country. Damages are occurred by landslide. It is increased annually by industrial development and extension of urban area. Serious damages occurred in Kangreng area of Gangwondo by typoon Rusa in August, 2002. Landslide hazard mapping needs to forecast and to manage landslide hazard area. GIS fits landslide hazard mapping, to reduce of time, manpower and costs, to investigate a board area, to do a spatial forecast model in study site. Variety of methods is for landslide hazard mapping. A study use root strength reinforcement model. This model use factors such as topography of slope, soil depth, soil properties, and vegetation of slope. Landslide hazard map is made by this model.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1097-1107
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• 2020

Assessment of soil carbon stock is essential for climate change mitigation and soil fertility. The digital soil mapping (DSM) is well known as a general technique to estimate the soil carbon stocks and upgrade previous soil maps. The aim of this study is to calculate the soil carbon stock in the top soil layer (0 to 30 cm) in Jeolla Province of South Korea using the DSM technique. To predict spatial carbon stock, we used Cubist, which a data-mining algorithm model base on tree regression. Soil samples (130 in total) were collected from three depths (0 to 10 cm, 10 to 20 cm, 20 to 30 cm) considering spatial distribution in Jeolla Province. These data were randomly divided into two sets for model calibration (70%) and validation (30%). The results showed that clay content, topographic wetness index (TWI), and digital elevation model (DEM) were the most important environmental covariate predictors of soil carbon stock. The predicted average soil carbon density was 3.88 kg·m-2. The R2 value representing the model's performance was 0.6, which was relatively high compared to a previous study. The total soil carbon stocks at a depth of 0 to 30 cm in Jeolla Province were estimated to be about 81 megatons.

• Journal of the Korea Computer Graphics Society
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• v.2 no.1
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• pp.15-23
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• 1996

Bump mapping is an elegant rendering technique to simulate wrinkled surfaces such as bark, which enables to produce more realistic image than texture-mapped one. This paper presents a new algorithm for bump mapping along with a hardware architecture to run our algorithm in real-time. The proposed approach is more efficient than previous one, and in particular, our hardware architecture is simpler to implement.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.187-194
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• 2024

For precise cardiac diagnostics and treatment, we introduce a novel method for patient-specific mapping between myocardial and coronary anatomy, leveraging local variations in myocardial thickness. This complex system integrates and automates multiple sophisticated components, including left ventricle segmentation, myocardium segmentation, long-axis estimation, coronary artery tracking, and advanced geodesic Voronoi distance mapping. It meticulously accounts for variations in myocardial thickness and precisely delineates the boundaries between coronary territories according to the conventional 17-segment myocardial model. Each phase of the system provides a step-by-step approach to automate coronary artery mapping onto the myocardium. This innovative method promises to transform cardiac imaging by offering highly precise, automated, and patient-specific analyses, potentially enhancing the accuracy of diagnoses and the effectiveness of therapeutic interventions for various cardiac conditions.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1358-1368
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• 2021

A research on agricultural automation is a main issues to overcome the shortage of labor in Korea. A sweet persimmon farmers need much time and labors for classifying profitable sweet persimmon and ill profitable products. In this paper, we propose a mixed two-step synthetic neural network model for efficiently classifying sweet persimmon images. In this model, we suggested a surface direction classification model and a quality screening model which constructed from image data sets. Also we studied Class Activation Mapping(CAM) for visualization to easily inspect the quality of the classified products. The proposed mixed two-step model showed high performance compared to the simple binary classification model and the multi-class classification model, and it was possible to easily identify the weak parts of the classification in a dataset.

• Korean Journal of Radiology
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• v.23 no.6
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• pp.664-673
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• 2022

Objective: To evaluate the performance of baseline clinical characteristics and pretherapeutic histogram parameters derived from T2 mapping of the extraocular muscles (EOMs) in the prediction of treatment response to intravenous glucocorticoid (IVGC) therapy for active and moderate-to-severe thyroid-associated ophthalmopathy (TAO) and to investigate the effect of fat-suppression (FS) in T2 mapping in this prediction. Materials and Methods: A total of 79 patients clinically diagnosed with active, moderate-to-severe TAO (47 female, 32 male; mean age ± standard deviation, 46.1 ± 10 years), including 43 patients with a total of 86 orbits in the responsive group and 36 patients with a total of 72 orbits in the unresponsive group, were enrolled. Baseline clinical characteristics and pretherapeutic histogram parameters derived from T2 mapping with FS (i.e., FS T2 mapping) or without FS (i.e., conventional T2 mapping) of EOMs were compared between the two groups. Independent predictors of treatment response to IVGC were identified using multivariable analysis. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performance of the prediction models. Differences between the models were examined using the DeLong test. Results: Compared to the unresponsive group, the responsive group had a shorter disease duration, lower kurtosis (FS-kurtosis), lower standard deviation, larger 75th, 90th, and 95th (FS-95th) T2 relaxation times in FS mapping and lower kurtosis in conventional T2 mapping. Multivariable analysis revealed that disease duration, FS-95th percentile, and FS-kurtosis were independent predictors of treatment response. The combined model, integrating all identified predictors, had an optimized area under the ROC curve of 0.797, 88.4% sensitivity, and 62.5% specificity, which were significantly superior to those of the imaging model (p = 0.013). Conclusion: An integrated combination of disease duration, FS-95th percentile, and FS-kurtosis was a potential predictor of treatment response to IVGC in patients with active and moderate-to-severe TAO. FS T2 mapping was superior to conventional T2 mapping in terms of prediction.

• Proceedings of the Optical Society of Korea Conference
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• 2007.07a
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• pp.259-260
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• 2007

In this paper, we propose a novel computational integral imaging reconstruction (CIIR) method using round-type mapping model. Proposed CIIP method can overcome problems of non-uniformly reconstructed images caused from the conventional method and improve the resoulution of 3-D images. To show the usefulness of the proposed method, both computational experiment and optical experiment are carried out and their results are presented.

• Progress in Superconductivity and Cryogenics
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• v.4 no.1
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• pp.124-128
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• 2002

A numerical model to obtain the temperature distribution in a radiation shield of cryogenic systems was proposed. Conformal mapping was used to transform the eccentric physical region of the upper plate to the concentric numerical region. The effects of the thickness of the radiation shield, the emissivities of the vacuum chamber and the radiation shield, and the eccentricity between the centers of the upper plate and the contact area with a cryocooler on the maximum temperature difference in a radiation shield were shown.

• Journal of the Korean earth science society
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• v.35 no.6
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• pp.412-421
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• 2014

In order to develop an effective mineral exploration technique, this study was carried out about the potential mapping of Gagok mine. The deposit model of Gagok mine is widely known. Based on the deposit model, we constructed mining indicator indices using related igneous rocks, faults, and carbonate rocks. By analyzing the spatial correlation between ore and indicator index structures, we decided the weighting values of indices according to the distance from the index structure. The 3D potential mapping was performed using 3D geological model and geological indices. The analyzed potential map verified that the locations and patterns of high potential regions of the results were well matched with those of the known ore bodies. Using the potential mapping results, we could effectively predict the location of a high potential area that has similar geological settings with ore.