• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.332-344
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• 2007

Various geophysical well logs have been made along the four deep wells in Pohang, Gyeongbuk. The primary focus of geophysical well loggings was to improve understanding the subsurface geologic structure, to evaluate in situ physical properties, and to estimate aquifer production zones using fluid temperature and conductivity gradient logs. Especially natural gamma logs interpreted with core logs of borehole BH-1 were useful to discriminate the lithology and to determine the lithologic sequences and boundaries consisting of semi-consolidated Tertiary sediments and intrusive rocks such as basic dyke and Cretaceous sediments. Cross-plot of physical properties inferred from geophysical well logs were used to identify rock types such as Cretaceous sandstone and mudstone, Tertiary sediments, rhyolite, and basic dyke. The temperature log indicated $82.51^{\circ}C$ at the depth of 1,981.3 meters in borehole BH-4. However, considering the temperature of borehole BH-2 measured under stable condition, we expect the temperature at the depth in borehole BH-4, if it is measured in stable condition, to be about 5 or $6^{\circ}C$ higher. Several permeable fractures also have been identified from temperature and conductivity gradient logs, and cutting logs.

• Journal of agriculture & life science
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• v.44 no.4
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• pp.9-20
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• 2010

This study was carried out to analyze the landslide characteristics and forest environment factors on the landslide area of Jeonlabuk-do province in korea. The results obtained from this study were summarized as follows; The total number of landslide occurrence was 182 areas. The average area of landslide scar was $1,859m^2$, average length of the landslides was 139m, average width was 13m. The landslides were highly occurred in igneous rock and coniferous. And also, slope gradient was $21{\sim}30^{\circ}$, aspect was NE, altitude was 401~500m, vertical and cross slope was concave (凹),stream order was 1 order, soil depth was 15m below, landslide type was linear, forest type was artificial. The relationship between landslide area and environmental factors was a positive correlation with cross slope (convex), position (upper), altitude (501m), forest type (coniferous), parent rock (sedimentary rock), D.B.H. (over 17cm), but was negative correlation with slope gradient ($31{\sim}40^{\circ}$), parent rock (igneous rock), D.B.H. (6~16cm).

• Geomechanics and Engineering
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• v.17 no.4
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• pp.343-354
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• 2019

The present study demonstrates the application of seismic petrophysics and amplitude versus angle (AVA) forward modeling to identify the reservoir fluids, discriminate their saturation levels and natural gas composition. Two case studies of the Lumshiwal Formation (mainly sandstone) of the Lower Cretaceous age have been studied from the Kohat Sub-basin and the Middle Indus Basin of Pakistan. The conventional angle-dependent reflection amplitudes such as P converted P ($R_{PP}$) and S ($R_{PS}$), S converted S ($R_{SS}$) and P ($R_{SP}$) and newly developed AVA attributes (${\Delta}R_{PP}$, ${\Delta}R_{PS}$, ${\Delta}R_{SS}$ and ${\Delta}R_{SP}$) are analyzed at different gas saturation levels in the reservoir rock. These attributes are generated by taking the differences between the water wet reflection coefficient and the reflection coefficient at unknown gas saturation. Intercept (A) and gradient (B) attributes are also computed and cross-plotted at different gas compositions and gas/water scenarios to define the AVO class of reservoir sands. The numerical simulation reveals that ${\Delta}R_{PP}$, ${\Delta}R_{PS}$, ${\Delta}R_{SS}$ and ${\Delta}R_{SP}$ are good indicators and able to distinguish low and high gas saturation with a high level of confidence as compared to conventional reflection amplitudes such as P-P, P-S, S-S and S-P. In A-B cross-plots, the gas lines move towards the fluid (wet) lines as the proportion of heavier gases increase in the Lumshiwal Sands. Because of the upper contacts with different sedimentary rocks (Shale/Limestone) in both wells, the same reservoir sand exhibits different response similar to AVO classes like class I and class IV. This study will help to analyze gas sands by using amplitude based attributes as direct gas indicators in further gas drilling wells in clastic successions.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.147-170
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• 2022

Although the number of patent which is one of the core outputs of technological innovation continues to increase, the number of low-value patents also hugely increased. Therefore, efficient evaluation of patents has become important. Estimation of patent lifespan which represents private value of a patent, has been studied for a long time, but in most cases it relied on a linear model. Even if machine learning methods were used, interpretation or explanation of the relationship between explanatory variables and patent lifespan was insufficient. In this study, patent lifespan (number of renewals) is predicted based on the idea that patent lifespan represents the value of the patent. For the research, 4,033,414 patents applied between 1996 and 2017 and finally granted were collected from USPTO (US Patent and Trademark Office). To predict the patent lifespan, we use variables that can reflect the characteristics of the patent, the patent owner's characteristics, and the inventor's characteristics. We build four different models (Ridge Regression, Random Forest, Feed Forward Neural Network, Gradient Boosting Models) and perform hyperparameter tuning through 5-fold Cross Validation. Then, the performance of the generated models are evaluated, and the relative importance of predictors is also presented. In addition, based on the Gradient Boosting Model which have excellent performance, Accumulated Local Effects Plot is presented to visualize the relationship between predictors and patent lifespan. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the evaluation reason of individual patents, and discuss applicability to the patent evaluation system. This study has academic significance in that it cumulatively contributes to the existing patent life estimation research and supplements the limitations of existing patent life estimation studies based on linearity. It is academically meaningful that this study contributes cumulatively to the existing studies which estimate patent lifespan, and that it supplements the limitations of linear models. Also, it is practically meaningful to suggest a method for deriving the evaluation basis for individual patent value and examine the applicability to patent evaluation systems.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.9 no.3
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• pp.137-152
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• 2004

The climatological characteristics of coastal zone over the southwestern coast of Korea peninsula were investigated using the data observed by AWS (automatic weather system) and 4 buoy points. Coastal zone is climatologically defined as the region bounded by the distinct contrast of temperature gradient and wind speed across coastline. In the southwest of peninsula four cross-lines consisted of AWS aligned with each buoy were selected as Geojedo buoy line, Geomundo buoy line, Chilbaldo buoy line and Dukjukdo buoy line. Analysis on the diurnal cycle and intra-month variation, monthly mean and maximum value, the temperature gradient with distance between buoy and each station and the accumulative frequency of wind speed were applied to find out the characteristics and the range of coast zone. The maximum ranges of coastal zone vary from offshore to Sanglim (about 34 km distance from coastline) for Geojedo buoy line, to Sunchun (about 52 km) for Geo-mundo buoy line, to Jaeundo (about 27 km) for chilbaldo buoy line and to Yongin (about 65 km) for Dukjukdo buoy line. The modification of coastal zone according to synoptic flow was investigated for the onshore, off-shore and calm cases. The ranges of coastal zone are significantly changed with the distance between 65∼90 km for the case of onshore. In addition, we tried to find out the variation of the wind and temperature and the wind ratio of wind speed at ocean to land stations along Geojedo buoy line during 12∼13 Sep. 2003 affected by typhoon (MAEMI).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.143-152
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• 2012

It is well-known that image matching is necessary for automatic generation of 3D data such as digital surface data from aerial images. Recently developed aerial digital cameras allow to capture multi-strip images with higher overlaps and less occluded areas than conventional analogue cameras and that much of researches on multi-image matching have been performed, particularly effective methods of measuring a similarity among multi-images using point features as well as linear features. This research aims to investigate similarity measuring methods such as SSD and SNCC incorporated into a area based multi-image matching method based on vertical line locus. In doing this, different similarity measuring entities such as grey value, grey value gradient, and average of grey value and its gradient are implemented and analyzed. Further, both dynamic and pre-fixed adaptive-window size are tested and analyzed in their behaviors in measuring similarity among multi-images. The aerial images used in the experiments were taken by a DMC aerial frame camera in three strips. The over-lap and side-lap are about 80% and 60%, respectively. In the experiment, it was found that the SNCC as similarity measuring method, the average of grey value and its gradient as similarity measuring entity, and dynamic adaptive-window size can be best fit to measuring area-based similarity in area based multi-image matching method based on vertical line locus.

• Journal of Korean Society of Forest Science
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• v.89 no.3
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• pp.397-404
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• 2000

This study was carried out to investigate the influence of the road structure and site conditions on side-ditch stability of forest road. For experimental purposes, the forest road in the Kwangrung Experimental Forest, Korea Forestry Research Institute, was chosen as a study site. A total of 556 plots wes set up as every longitudinal gradient changing points by belt-transect method. Data of 10 road structural characteristics and side-ditch stability were collected from each plot and analysed by Quantification II. The main factors in order of partial correlation coefficient were longitudinal gradient, road position, inclination of cut-slope, constituent material of cut-slopes, distance of surface flow, cross-sectional shape of road, pavement material, vegetation of cut-slopes and length of cut-slope. The erosion of side-ditch of forest road occurred in the following cases; more than 8% of the longitudinal gradient, road position of hill under side and foot hill, more than $50^{\circ}$ of inclination of cut-slope, constituent material of cut-slopes of hard soil and gravel soil, more than 80m of distance of surface flow, pavement material with earth or gravel, more than medium covered of vegetation of cut-slopes, and the straight and convex form of road-bed.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.97-117
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• 2021

Predicting term deposit subscriptions is one of representative financial marketing in banks, and banks can build a prediction model using various customer information. In order to improve the classification accuracy for term deposit subscriptions, many studies have been conducted based on machine learning techniques. However, even if these models can achieve satisfactory performance, utilizing them is not an easy task in the industry when their decision-making process is not adequately explained. To address this issue, this paper proposes an explainable scheme for term deposit subscription forecasting. For this, we first construct several classification models using decision tree-based ensemble learning methods, which yield excellent performance in tabular data, such as random forest, gradient boosting machine (GBM), extreme gradient boosting (XGB), and light gradient boosting machine (LightGBM). We then analyze their classification performance in depth through 10-fold cross-validation. After that, we provide the rationale for interpreting the influence of customer information and the decision-making process by applying Shapley additive explanation (SHAP), an explainable artificial intelligence technique, to the best classification model. To verify the practicality and validity of our scheme, experiments were conducted with the bank marketing dataset provided by Kaggle; we applied the SHAP to the GBM and LightGBM models, respectively, according to different dataset configurations and then performed their analysis and visualization for explainable term deposit subscriptions.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.1
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• pp.17-28
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• 2019

In the financial investment management strategy, the distributed investment selecting and combining various financial assets is called portfolio management theory. In recent years, the blockchain based financial assets, such as cryptocurrencies, have been traded on several well-known exchanges, and an efficient portfolio management approach is required in order for investors to steadily raise their return on investment in cryptocurrencies. On the other hand, deep learning has shown remarkable results in various fields, and research on application of deep reinforcement learning algorithm to portfolio management has begun. In this paper, we propose an efficient financial portfolio investment management method based on Asynchronous Advantage Actor-Critic (A3C), which is a representative asynchronous reinforcement learning algorithm. In addition, since the conventional cross-entropy function can not be applied to portfolio management, we propose a proper method where the existing cross-entropy is modified to fit the portfolio investment method. Finally, we compare the proposed A3C model with the existing reinforcement learning based cryptography portfolio investment algorithm, and prove that the performance of the proposed A3C model is better than the existing one.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.1
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• pp.21-28
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• 2000

Although commercial PIV systems have been widely used for the non-intrusive velocity field measurement of fluid flows, they are still under development and have considerable room for improvement. In this study, a single-frame double-exposure PIV system using a high-resolution CCD camera was developed. A pulsed Nd:Yag laser and high-resolution CCD camera were synchronized by a home-made control circuit. In order to resolve the directional ambiguity problem encountered in the single-frame PIV technique, the second particle image was genuinely shifted in the CCD sensor array during the time interval dt. The velocity vector field was determined by calculating the displacement vector at each interrogation window using cross-correlation with 50% overlapping. In order to check the effect of spatial resolution of CCD camera on the accuracy of PIV velocity field measurement, the developed PIV system with three different resolution modes of the CCD camera (512 ${\times}$ 512, lK ${\times}$ IK, 2K ${\times}$ 2K) was applied to a turbulent flow which simulate the Zn plating process of a steel strip. The experimental model consists of a snout and a moving belt. Aluminum flakes about $1{\mu}m$ diameter were used as scattering particles for the liquid flow in the zinc pot and the gas flow above the zinc surface was seeded with atomized olive oil with an average diameter of 1-$3{\mu}m$. Velocity field measurements were carried out at the strip speed $V_s$=1.0 m/s. The 2K ${\times}$ 2K high-resolution PIV technique was significantly superior compared to the smaller pixel resolution PIV system. For the cases of 512 ${\times}$ 512 and 1K ${\times}$ 1K pixel resolution PIV system, it was difficult to get accurate flow structure of viscous flow near the wall and small vortex structure in the region of large velocity gradient.