• Geomechanics and Engineering
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• v.13 no.6
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• pp.1045-1055
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• 2017

Tensile strength is considered key properties for characterizing rock material in engineering project. It is determined by direct and indirect methods. Point load test is a useful testing method to estimate the tensile strengths of rocks. In this paper, the effects of rock shape on the point load index of gypsum are investigated by PFC2D simulation. For PFC simulating, initially calibration of PFC was performed with respect to the Brazilian experimental data to ensure the conformity of the simulated numerical models response. In second step, nineteen models with different shape were prepared and tested under point load test. According to the obtained results, as the size of the models increases, the point load strength index increases. It is also found that the shape of particles has no major effect on its tensile strength. Our findings show that the dominant failure pattern for numerical models is breaking the model into two pieces. Also a criterion was rendered numerically for determination of tensile strength of gypsum. The proposed criteria were cross checked with the results of experimental point load test.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.72.3-73
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• 2021

Baryon Acoustic Oscillations (BAO) are caused by acoustic density waves in the early universe and act as a standard ruler in the clustering pattern of galaxies in the late Universe. Measuring the BAO feature in the 2-point correlation function of a sample of galaxies allows us to estimate cosmological distances to the galaxies mean redshift, , which is important for testing and constraining the cosmology model. The BAO feature is also expected to appear in the higher order statistics. In this work we measure the generalized spatial N-point point correlation functions up to 4th order. We made measurements of the 2, 3, and 4-point correlation functions in the SDSS-III DR12 CMASS data, comprising of 777,202 galaxies. The errors and covariances matrices were estimated from 500 mock catalogues. We created a theoretical model for these statistics by measuring the N-point functions in halo catalogues produced by the approximate Lagrangian perturbation theory based simulation code, PINOCCHIO. We created simulations using initial conditions with and without the BAO feature. We find that the BAO is detected to high significance up to the 4-point correlation function.

• Journal of the Korean Society of Safety
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• v.32 no.6
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• pp.150-156
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• 2017

A frozen road surface increases traffic accidents during the winter season. Hence, information on easily-frozen road sections and their specificities are required to prevent traffic accidents. Frozen road surfaces are determined by equipment measuring road surface temperatures. However, there are limitations in investigating the entire road network. Therefore, it is imperative to develop new methods that effectively determine road surface freezing risks. Meteorologically, road surfaces are frozen when the actual temperature cools down to the dew point temperature. Under this condition, there is likely to be frost if relative humidity reaches 100% and frozen road surfaces as the temperature gets lower. Meteorological characteristics give us an alternative to a direct measurement road surface temperature to estimate risks of road surface freezing. Based on the clues, the relationship between severity of traffic accidents and temperature changes is empirically investigated using Paju weather data. The results reveal that as the temperature gets lower and changes in current temperature are relatively small, the severity of traffic accidents become higher. In addition, the same is true when the difference between current temperature and the dew point temperature is relatively small, as it increases possibilities of road surface freezing. Future studies must investigate how current temperature and the dew point temperature affect road surface freezing and thereby establish a time-space scope to estimate possible road surface freezing sections using only weather and road material type data. This would provide invaluable information for predicting and preventing frozen road accidents based on weather patterns.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.257-265
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• 2013

As evaluating the health literacy is getting important, various measures for evaluation are being developed. Nevertheless, discussions about developing proper measures in Korean are still inactive. Therefore in this paper, we proposed Korean REALM (rapid estimate of adult literacy in medicine) measure that is composed of five point scale and investigated about its validity. As a result, we could find that Korean REALM measure which is composed of five point scale has high reliability, and that it formed one dimension as a result of factor analysis. Positive responses were lower than two point scale and correlation coefficient with NVS (the newest vital sign) appeared statistically significant. Therefore, we could conclude that Korean REALM measure that is composed of five point scale is a valid measurement. Furthermore, there were statistically significant differences between general students and department of nursing students about health literacy.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.2
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• pp.255-260
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• 2017

In Korea, traffic accidents between pedestrians and vehicles in 2015 account for 38.8% of all accidents. This study proposes a system design that can measure the risk of conflict between a vehicle and a pedestrian. Firstly the systemdetect and estimate the position, speed, and directional data of the vehicle and the pedestrian. And then it estimate the conflict point between a vehicle and a pedestrian. The risk of conflict is quantified by estimating the pedestrian safety margin (PSM), which is the time difference between the arrival of the pedestrian at the crossing point to the point of conflict and the vehicle approaching the point. In this system each data is acquired through an external monitoring based evaluation module and an individual wearing module. In the future, such a system can be used for decision making such as the design of road hazard improvement facilities and the designation of the elderly protection area.

• Journal of Ecology and Environment
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• v.41 no.2
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• pp.34-44
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• 2017

Background: Monitoring terrestrial vegetation cover condition is important to evaluate its current condition and to identify potential vulnerabilities. Due to simplicity and low cost, point intercept method has been widely used in evaluating grassland surface and quantifying cover conditions. Field-based digital photography method is gaining popularity for the purpose of cover estimate, as it can reduce field time and enable additional analysis in the future. However, the caveats and uncertainty among field-based vegetation cover estimation methods is not well known, especially across a wide range of cover conditions. We compared cover estimates from point intercept and digital photography methods with varying sampling intensities (25, 49, and 100 points within an image), across 61 transects in typical steppe, forest steppe, and desert steppe in central Mongolia. We classified three photosynthetic groups of cover important to grassland ecosystem functioning: photosynthetic vegetation, non-photosynthetic vegetation, and bare soil. We also acquired normalized difference vegetation index from satellite image comparison with the field-based cover. Results: Photosynthetic vegetation estimates by point intercept method were correlated with normalized difference vegetation index, with improvement when non-photosynthetic vegetation was combined. For digital photography method, photosynthetic and non-photosynthetic vegetation estimates showed no correlation with normalized difference vegetation index, but combining of both showed moderate and significant correlation, which slightly increased with greater sampling intensity. Conclusions: Results imply that varying greenness is playing an important role in classification accuracy confusion. We suggest adopting measures to reduce observer bias and better distinguishing greenness levels in combination with multispectral indices to improve estimates on dry matter.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.367-376
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• 1997

Consider the accelerated sequential procedure of Hall(1983). Second order asymptotic expression of well behaved functions of the stopping variable. The results is demonstrated by working out several point and interval estimation problems.

• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.281-301
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• 2004

In this paper we consider the change point problem in a sequence of univariate normal observations. We want to know whether there is any change point or not. In case a change point exists, we will identify its change type. Namely, it can be a mean change, a variance change, or both the mean and variance change. The intrinsic Bayes factors of Berger and Pericchi (1996, 1998) are used to find the type of optimal change model. The Gibbs sampling including the Metropolis-Hastings algorithm is used to estimate all the parameters in the change model. These methods are checked via simulation and applied to the winter average temperature data in Seoul.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.3
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• pp.107-111
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• 2021

A 3D point cloud map is an essential elements in various fields, including precise autonomous navigation system. However, generating a 3D point cloud map using a single sensor has limitations due to the price of expensive sensor. In order to solve this problem, we propose a precise 3D mapping system using low-cost sensor fusion. Generating a point cloud map requires the process of estimating the current position and attitude, and describing the surrounding environment. In this paper, we utilized a commercial visual-inertial odometry sensor to estimate the current position and attitude states. Based on the state value, the 2D LiDAR measurement values describe the surrounding environment to create a point cloud map. To analyze the performance of the proposed algorithm, we compared the performance of the proposed algorithm and the 3D LiDAR-based SLAM (simultaneous localization and mapping) algorithm. As a result, it was confirmed that a precise 3D point cloud map can be generated with the low-cost sensor fusion system proposed in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.834-841
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• 2020

Among the autonomous driving systems based on visual sensors, the control method using a vanishing point is the most general method for autonomous driving. However, if the lane is lost or does not exist, it is very difficult to detect this and estimate the vanishing point. In this paper, we predict the vanishing point of the road and the vanishing point lines on the left and right sides using CNN for the camera image and design the steering controller for autonomous driving from the predicted results. As a result of the simulation, it was confirmed that the proposed method well tracked the center of the road regardless of the presence or absence of a solid lane, and was superior to the control method using a general method using the vanishing point.