• Journal of the Speleological Society of Korea
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• v.14 no.15
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• pp.42-90
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• 1987

Lee, Moon Won reported by 63 kinds lescribing the petrography and bulk chemical Composition in Petrology of Cheju volcanic island. The total Chemical Composition data was analyzed by the program of FORTRAN77. First, the Conversition equations and the scatter diagram were examined to the analysis, by the least square method. Next, a statistical data requested a mean Value, maximum value, minimum value, the range, the standard deviation, the variance, the Standord Error and the Coefficient of variation. In the standard deviation, a small Composition is MnO and P$_2$O$\sub$5/, a large Composition is SiO$_2$, Mgo and FeO. The Standard error and the variance were the tandency looked like the Standard deviation well. However, the Coefficient Variation differs from the Standard deviation. Where, a large Coefficient of variation are H$_2$O$\^$-/ and H$_2$O$\^$+/, a small Coefficient of variation are Al$_2$O$_3$ and SiO$_2$. The Correlation of Coefficient Can be Calculated numerically from the relation between SiO$_2$, Al$_2$O$_3$ and TiO$_2$ to other Compositions.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.35.2-35.2
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• 2016

We present a census of AGN-driven gas outflows based on the kinematics of ionized gas and stars, using a large sample of ~11,000 emission line galaxies at z < 0.3, selected from SDSS. First, a broad correlation between gas and stellar velocity dispersions indicates that the bulge gravitational potential plays a main role in determining the ionized gas kinematics. However, the velocity dispersion of the [OIII] emission line is larger than stellar velocity dispersion by a factor of 1.3-1.4, suggesting that the non-gravitational (non-virial) component, i.e., outflows, is almost comparable to the gravitational component. Second, gas-to-stellar velocity dispersion ratio increases with both AGN luminosity and Eddington ratio, suggesting that non-gravitational kinematics are clearly linked to AGN accretion. The distribution in the [OIII] velocity - velocity dispersion diagram dramatically expands toward large values with increasing AGN luminosity, implying that the launching velocity of gas outflows increases with AGN luminosity. Third, the fraction of AGNs with a signature of the non-gravitational kinematics, steeply increases with AGN luminosity and Eddington ratio, while the majority of luminous AGNs presents the non-gravitational kinematics in the [OIII] profile. These results suggest that ionized gas outflows are prevalent among type 2 AGNs. On the other hand, we find no strong trend of the [OIII] kinematics with radio luminosity, once we remove the effect of the bulge gravitational potential, indicating that ionized gas outflows are not directly related to radio activity for the majority of type 2 AGNs. We will discuss the implication of these results for AGN feedback in the local universe.

• Journal of Environmental Science International
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• v.19 no.10
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• pp.1271-1281
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• 2010

This study aims to implement the modeling of selected substances for the evaluation of Atmospheric Environmental Capacity by means of the data of 2006 atmospheric pollution substance emissions. As a result, it turned out that the substance with the concentration higher than Atmospheric Environmental standard concentration was NO2, and 17.6% of the total regions researched turned out to exceed the standard concentration. In addition, set was the targeted amount to be reduced in the areas where the upper limit of emission per unit lattice was exceeded, and the model was adopted accordingly. As a result, it turned out that about 80% of the actual emission should be reduced to meet the 2006 Atmospheric Environmental standard over the Daegu. In reality, it is impossible to reduce 80% of the actual emission. Thus, the same ratio of reduction was applied in all of the Daegu regions, and the modeling was applied. The results are as follows: When 30% was reduced, the level went down to 50 ppb, which is as high as 2006 Atmospheric Environmental standard; when 50% was reduced, the level went down to 30 ppb, which is as high as 2007 Atmospheric Environmental standard.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.15-22
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• 2006

This paper presents a novel signal tracking algorithm for GNSS receivers using a MLE technique. In order to perform a robust signal tracking in severe signal environments, e.g., high dynamics for navigation vehicles or weak signals for indoor positioning, the MLE based signal tracking approach is adopted in the paper. With assuming white Gaussian additive noise, the cost function of MLE is expanded to the cost function of NLSE. Efficient and practical approach for Doppler frequency tracking by the MLE is derived based on the assumption of code-free signals, i.e., the cost function of the MLE for carrier Doppler tracking is used to derive a discriminator function to create error signals from incoming and reference signals. The use of the MLE method for carrier tracking makes it possible to generalize the MLE equation for arbitrary codes and modulation schemes. This is ideally suited for various GNSS signals with same structure of tracking module. This paper proposes two different types of MLE based tracking method, i.e., an iterative batch processing method and a non-iterative feed-forward processing method. The first method is derived without any limitation on time consumption, while the second method is proposed for a time limited case by using a 1st derivative of cost function, which is proportional to error signal from discriminators of conventional tracking methods. The second method can be implemented by a block diagram approach for tracking carrier phase, Doppler frequency and code phase with assuming no correlation of signal parameters. Finally, a state space form of FLL/PLL/DLL is adopted to the designed MLE based tracking algorithm for reducing noise on the estimated signal parameters.

• Structural Engineering and Mechanics
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• v.85 no.5
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• pp.679-691
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• 2023

Many codes allow designers to use the bending moment diagram computed by elastic analysis and modify it by a certain amount of moment redistribution (MR) to account for plastic behaviour of continuous beams. However, several researchers indicated that the MR at the ultimate limit state (𝛽_u) for some beams deviate significantly from the specified values of various codes. This paper examines the applicability of the provisions on 𝛽_u in ACI 318-19 and Eurocode 2 through numerical investigations and comprehensively explores the influencing factors. The results show that some parameters not considered in those codes influence 𝛽_u to a certain extent, where the ratio of tensile reinforcement ratio at intermediate support to tensile reinforcement ratio at midspan (𝜌_s1/𝜌_s2) and load type are crucial parameters to consider. The specific combination of these two parameters may make the codes overestimate or significantly underestimate the 𝛽_u. On the other hand, the yield state of both critical sections is found to have an important influence on the influence degree of each parameter on 𝛽_u. The yield conditions are investigated, and an empirical judgment equation is proposed. In addition, the influence laws of the critical parameters on 𝛽_u have been further proved by theoretical derivation. Finally, due to 𝜀_t is found to have a better linear correlation with 𝛽_u than x_u/d, equations as a function of 𝜀_t for predicting the 𝛽_u of continuous beams under the two loads are proposed, respectively.

• Geomechanics and Engineering
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• v.34 no.3
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• pp.267-284
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• 2023

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.

• Geomechanics and Engineering
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• v.31 no.2
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• pp.129-147
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• 2022

The properties of soil are naturally highly variable and thus, to ensure proper safety and reliability, we need to test a large number of samples across the length and depth. In pile foundations, conducting field tests are highly expensive and the traditional empirical relations too have been proven to be poor in performance. The study proposes a state-of-art Particle Swarm Optimization (PSO) hybridized Artificial Neural Network (ANN), Extreme Learning Machine (ELM) and Adaptive Neuro Fuzzy Inference System (ANFIS); and comparative analysis of metaheuristic models (ANN-PSO, ELM-PSO, ANFIS-PSO) for prediction of bearing capacity of pile foundation trained and tested on dataset of nearly 300 dynamic pile tests from the literature. A novel ensemble model of three hybrid models is constructed to combine and enhance the predictions of the individual models effectively. The authenticity of the dataset is confirmed using descriptive statistics, correlation matrix and sensitivity analysis. Ram weight and diameter of pile are found to be most influential input parameter. The comparative analysis reveals that ANFIS-PSO is the best performing model in testing phase (R² = 0.85, RMSE = 0.01) while ELM-PSO performs best in training phase (R² = 0.88, RMSE = 0.08); while the ensemble provided overall best performance based on the rank score. The performance of ANN-PSO is least satisfactory compared to the other two models. The findings were confirmed using Taylor diagram, error matrix and uncertainty analysis. Based on the results ELM-PSO and ANFIS-PSO is proposed to be used for the prediction of bearing capacity of piles and ensemble learning method of joining the outputs of individual models should be encouraged. The study possesses the potential to assist geotechnical engineers in the design phase of civil engineering projects.

• Journal of the Korean Institute of Gas
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• v.27 no.3
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• pp.35-40
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• 2023

In order to prevent an ammonia container from bursting under conditions such as overcharging and abnormal temperature rise, it is necessary to prepare accident prevention measures through analysis of the operating mechanism of the Thermally Activated Pressure Relief Devices (TPRD) attached to the container. In this study, stress analysis acting on the ammonia container under pressurized conditions, density change analysis according to temperature change, and correlation between container filling amount and temperature and pressure change were presented. In addition, the maximum filling amount of the ammonia container was calculated, and the temperature and pressure at the filling amount were calculated through the phase equilibrium diagram. Based on this, the appropriate melting point of the Thermally Activated Pressure Relief Devices was derived and verified through a melting temperature experiment. Based on the results of this study, conditions for preventing ammonia container rupture accidents were suggested.

• Advances in materials Research
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• v.13 no.1
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• pp.63-86
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• 2024

Asphalt concrete (AC), is a mixture of bitumen and aggregates, which is very sensitive in the design of flexible pavement. In this study, the Marshall stability of the glass and carbon fiber bituminous concrete was predicted by using Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and M5P Tree machine learning algorithms. To predict the Marshall stability, nine inputs parameters i.e., Bitumen, Glass and Carbon fibers mixed in 100:0, 75:25, 50:50, 25:75, 0:100 percentage (designated as 100GF:0CF, 75GF:25CF, 50GF:50 CF, 25GF:75CF, 0GF:100CF), Bitumen grade (VG), Fiber length (FL), and Fiber diameter (FD) were utilized from the experimental and literary data. Seven statistical indices i.e., coefficient of correlation (CC), mean absolute error (MAE), root mean squared error (RMSE), relative absolute error (RAE), root relative squared error (RRSE), Scattering index (SI), and BIAS were applied to assess the effectiveness of the developed models. According to the performance evaluation results, Artificial neural network (ANN) was outperforming among other models with CC values as 0.9147 and 0.8648, MAE values as 1.3757 and 1.978, RMSE values as 1.843 and 2.6951, RAE values as 39.88 and 49.31, RRSE values as 40.62 and 50.50, SI values as 0.1379 and 0.2027 and BIAS value as -0.1 290 and -0.2357 in training and testing stage respectively. The Taylor diagram (testing stage) also confirmed that the ANN-based model outperforms the other models. Results of sensitivity analysis showed that the fiber length is the most influential in all nine input parameters whereas the fiber combination of 25GF:75CF was the most effective among all the fiber mixes in Marshall stability.

• Journal of the Korean earth science society
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• v.28 no.3
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• pp.324-342
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• 2007

This study reports petrography and geochemical characteristics of the basalt lava flows in Seongsan-Ilchulbong area, the easternpart of Jeju island, Korea, to understand the evolutionary processes of magma. Basalt lavas are classified into the Pyoseon-ri basalt and the Seongsan-ri basalt. The Pyoseon-ri basalt is dark-gray colored with many vescicles, and mainly consists of olivine, feldspar and rarely of clinopyroxene as phenocrysts. The Seongsan-ri basalt is largely aphanitic basalt and bright-gray colored, divided into two lava-flow units: lower lava flow (B1) and upper lava flow (B2) by the intercalated yellowish lapillistone and paleosol. The lavas plotted into sub-alkaline tholeiitic basalt and alkaline basalt series. The tholeiitic basalts have characteristically higher $SiO_2,\;FeO^T$, and CaO contents, but lower $TiO_2,\;K_2O,\;P_2O_5$ and other incompatible elements compared to the alkali basalts. The tholeiitic basalts have higher $SiO_2$ to the same MgO contents than the alkalic basalts. The contents of Ni, Cr, and MgO show a strong positive correlation, which indicates that low-MgO phases like plagioclase and titanomagnetite were important during the differentiation of magma. The contents of incompatible elements against that of Th show a strong positive correlation. The chondrite-nomalized REE patterns of tholeiitic and alkalic basalts are subparallel each other. LREEs contents of the former are lower than, but HREEs contents are similar to the latter. They both are similar to their K/Ba ratios. The primitive-mantle normalized spider diagram demonstrates that the contents of Ba and Th of all basaltic magma are enriched, and yet Cr, Ni are depleted. The tholeiitic and alkalic basalts may be originated from a different degree of the partial melting of the same mantle material source, and one shows a higher degree of the partial melting than the other.