• The Journal of Engineering Geology
• /
• v.32 no.3
• /
• pp.377-388
• /
• 2022

Recently, several studies have utilized machine learning to efficiently and accurately analyze seismic data that are exponentially increasing. In this study, we expand earthquake information such as occurrence time, hypocentral location, and magnitude to produce a dataset for applying to machine learning, reducing the dimension of the expended data into dominant features through principal component analysis. The dimensional extended data comprises statistics of the earthquake information from the Global Centroid Moment Tensor catalog containing 36,699 seismic events. We perform data preprocessing using standard and max-min scaling and extract dominant features with principal components analysis from the scaled dataset. The scaling methods significantly reduced the deviation of feature values caused by different units. Among them, the standard scaling method transforms the median of each feature with a smaller deviation than other scaling methods. The six principal components extracted from the non-scaled dataset explain 99% of the original data. The sixteen principal components from the datasets, which are applied with standardization or max-min scaling, reconstruct 98% of the original datasets. These results indicate that more principal components are needed to preserve original data information with even distributed feature values. We propose a data processing method for efficient and accurate machine learning model to analyze the relationship between seismic data and seismic behavior.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.3
• /
• pp.129-138
• /
• 2014

This paper proposes a fast intra prediction method to reduce encoding time for the HEVC(high-efficiency video coding) encoder. The proposed fast Intra prediction method uses quadtree structure and SATD(Sum of Absolute Transformed Differences). In HEVC, a $8{\times}8$ SATD value using $8{\times}8$ hadamard transform is used to calculate a SATD value for $8{\times}8$ or larger blocks. The proposed method calculates the best SATD value by using each $8{\times}8$ SATD result in $16{\times}16$ or larger blocks. After that, the proposed method removes a candidate mode for RDO(Rate-Distortion Optimization) based on comparing SATD of the candidate mode and the best SATD. By removing candidate modes, the proposed method reduces the operation of RDO and reduces total encoding time. In $8{\times}8$ block, the proposed method uses additional $4{\times}4$ SATD to calculat the best SATD. The experimental results show that the proposed method achieved 5.08% reduction in encoding time compared to the HEVC test model 12.1 encoder with almost no loss in compression performance.

• Korea-Australia Rheology Journal
• /
• v.21 no.1
• /
• pp.59-69
• /
• 2009

The prediction of pressure drop for a droplet flow in a confined micro channel is presented using FE-FTM (Finite Element - Front Tracking Method). A single droplet is passing through 5:1:5 contraction - straight narrow channel - expansion flow domain. The pressure drop is investigated especially when the droplet flows in the straight narrow channel. We explore the effects of droplet size, capillary number (Ca), viscosity ratio ($\chi$) between droplet and medium, and fluid elasticity represented by the Oldroyd-B constitutive model on the excess pressure drop (${\Delta}p^+$) against single phase flow. The tightly fitted droplets in the narrow channel are mainly considered in the range of $0.001{\leq}Ca{\leq}1$ and $0.01{\leq}{\chi}{\leq}100$. In Newtonian droplet/Newtonian medium, two characteristic features are observed. First, an approximate relation ${\Delta}p^+{\sim}{\chi}$ observed for ${\chi}{\geq}1$. The excess pressure drop necessary for droplet flow is roughly proportional to $\chi$. Second, ${\Delta}p^+$ seems inversely proportional to Ca, which is represented as ${\Delta}p^+{\sim}Ca^m$ with negative m irrespective of $\chi$. In addition, we observe that the film thickness (${\delta}_f$) between droplet interface and channel wall decreases with decreasing Ca, showing ${\delta}_f{\sim}Ca^n$ Can with positive n independent of $\chi$. Consequently, the excess pressure drop (${\Delta}p^+$) is strongly dependent on the film thickness (${\delta}_f$). The droplets larger than the channel width show enhancement of ${\Delta}p^+$, whereas the smaller droplets show no significant change in ${\Delta}p^+$. Also, the droplet deformation in the narrow channel is affected by the flow history of the contraction flow at the entrance region, but rather surprisingly ${\Delta}p^+$ is not affected by this flow history. Instead, ${\Delta}p^+$ is more dependent on ${\delta}_f$ irrespective of the droplet shape. As for the effect of fluid elasticity, an increase in ${\delta}_f$ induced by the normal stress difference in viscoelastic medium results in a drastic reduction of ${\Delta}p^+$.

• Progress in Superconductivity and Cryogenics
• /
• v.15 no.2
• /
• pp.34-38
• /
• 2013

AC Losses for face to face stacks of four identical coated conductors (CCs) were numerically calculated using the H-formulation combined with the E-J power law and the Kim model. The motive sample was the face to face stack of four 2 mm-wide CC tapes with 2 ${\mu}m$ thick superconducting layer of which the critical current density, $J_c$, was $2.16{\times}10^6A/cm^2$ on IBAD-MgO template, which was suggested for the mitigation of ac loss as a round shaped wire by Korea Electrotechnology Research Institute. For the calculation the cross section of the stack was simply modeled as vertically aligned 4 rectangles of superconducting (SC) layers with $E=E_o(J(x,y,t)/J_c(B))^n$ in x-y plane where $E_o$ was $10^{-6}$ V/cm, $J_c$(B) was the field dependence of current density and n was 21. The field dependence of the critical current of the sample measured in four-probe method was employed for $J_c$(B) in the equation. The model was implemented in the finite element method program by commercial software. The ac loss properties for the stacks were compared with those of single 4 cm-wide SC layers with the same critical current density or the same critical current. The constraint for the simulation was imposed in two different ways that the total current of the stack obtained by integrating J(x,y,t) over the cross sections was the same as that of the applied transport current: one is that one fourth of the external current was enforced to flow through each SC. In this case, the ac loss values for the stacks were lower than those of single wide SC layer. This mitigation of the loss is attributed to the reduction of the normal component of the magnetic field near the SC layers due to the strong expulsion of the magnetic field by the enforced transport current. On the contrary, for the other case of no such enforcement, the ac loss values were greater than those of single 4cm-wide SC layer and. In this case, the phase difference of the current flowing through the inner and the outer SC layers of the stack was observed as the transport current was increased, which was a cause of the abrupt increase of ac loss for higher transport current.

• Journal of Broadcast Engineering
• /
• v.12 no.6
• /
• pp.611-623
• /
• 2007

The H.264|AVC standard incorporates an intra prediction tool into inter frame coding. However, this leads to excessive amount of increase in encoding time, thus resulting in the difficulty in real-time implementation of software encoders. In this paper, we first propose an early decision on intra prediction coding and a fast intra prediction method using the characteristics of block contents and the context of neighboring block modes for the intra prediction in the inter frame coding of H.264/AVC. Basically, the proposed methods determine a skip condition on whether the $4{\times}4$ intra prediction is to be used in the inter frame coding by considering the content characteristics of each block to be encoded and the context of its neighboring blocks. The performance of our proposed methods is compared with the Joint Model reference software version 11.0 of H.264|AVC. The experimental results show that our proposed methods allow for 41.63% reduction in the total encoding time with negligible amounts of PSNR drops and bitrate increases, compared to the original Joint Model reference software version 11.0.

• Explosives and Blasting
• /
• v.38 no.4
• /
• pp.16-25
• /
• 2020

Multi-setting smart-investigation of the ground and large uncharged hole boring (MSP) method to reduce the blast-induced vibration in a tunnel excavation is carried out over 50m of long-distance boring in a horizontal direction and thus has been accompanied by deviations in boring alignment because of the heavy and one-directional rotation of the rod. Therefore, the deviation has been adjusted through the boring machine's variable setting rely on the previous construction records and expert's experience. However, the geological characteristics, machine conditions, and inexperienced workers have caused significant deviation from the target alignment. The excessive deviation from the boring target may cause a delay in the construction schedule and economic losses. A deep learning-based prediction model has been developed to discover an ideal initial setting of the MSP machine. Dropout, early stopping, pre-training techniques have been employed to prevent overfitting in the training phase and, significantly improved the prediction results. These results showed the high possibility of developing the model to suggest the boring machine's optimum initial setting. We expect that optimized setting guidelines can be further developed through the continuous addition of the data and the additional consideration of the other factors.

• Journal of the Korean GEO-environmental Society
• /
• v.21 no.12
• /
• pp.23-28
• /
• 2020

As a result of a suite of laboratory tests undertaken to suggest a rational method for the estimation of infiltration capacity, it is found that the infiltration rate tends to increase as the soil unit weight decreases while it tends to increase as the rainfall intensity increases. Comparative analyses for infiltration curves employing the reduction constant of initial infiltration capacity (α coefficient) that was suggested in this study has reasonably captured the time dependent variation of infiltration capacity. Consequently this study has presented an experimental model for the estimation of infiltration capacity to improve the Horton infiltration capacity curve that has been widely used for estimation of the infiltration capacity and amount of infiltration for its application to sandy soils.

• Computers and Concrete
• /
• v.19 no.6
• /
• pp.711-716
• /
• 2017

This paper presents a method using artificial neural networks (ANNs) to predict the residual moment capacity of thermally insulated reinforced concrete (RC) beams exposed to fire. The use of heat resistant insulation material protects concrete beams against the harmful effects of fire. If it is desired to calculate the residual moment capacity of the beams in this state, the determination of the moment capacity of thermally insulated beams exposed to fire involves several consecutive calculations, which is significantly easier when ANNs are used. Beam width, beam effective depth, fire duration, concrete compressive and steel tensile strength, steel area, thermal conductivity of insulation material can influence behavior of RC beams exposed to high temperatures. In this study, a finite difference method was used to calculate the temperature distribution in a cross section of the beam, and temperature distribution, reduction mechanical properties of concrete and reinforcing steel and moment capacity were calculated using existing relations in literature. Data was generated for 336 beams with different beam width ($b_w$), beam account height (h), fire duration (t), mechanical properties of concrete ($f_{cd}$) and reinforcing steel ($f_{yd}$), steel area ($A_s$), insulation material thermal conductivity (kinsulation). Five input parameters ($b_w$, h, $f_{cd}$, $f_{yd}$, $A_s$ and $k_{insulation}$) were used in the ANN to estimate the moment capacity ($M_r$). The trained model allowed the investigation of the effects on the moment capacity of the insulation material and the results indicated that the use of insulation materials with the smallest value of the thermal conductivities used in calculations is effective in protecting the RC beam against fire.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.32-32
• /
• 2017

2012년부터 도입된 "신재생에너지 의무할당제(RPS)"로 인하여 500MW이상의 설비 용량을 갖춘 발전소의 경우 총발전량에서 일정 비율을 신재생에너지로 공급하여야 한다. 이러한 신재생에너지 중 농업부산물은 목질계 바이오매스의 한 종류로 '탄소중립(Carbon Neutral)' 연료이며 기존 화석연료와 혼소로 활용 할 수 있는 장점을 지니고 있다. 그러나 낮은 발열량, 운송 및 저장비용, 일정하지 않은 연소특성의 문제로 인하여 대부분 노지에 방치되거나 버려지고 있다. 이러한 버려지는 농업부산물을 효율적으로 활용하기 위한 방법 중 하나로 반탄화(Torrefacation) 처리가 대두되고 있다. 반탄화 처리 시, 발열량이 증대되며, 저장과 이송에서의 이점을 갖게 된다. 그러나, 반탄화는 공정 과정중 질량손실에 따른 에너지 총량의 감소한다는 단점을 가지고 있다. 이에 본 연구에서는 효율적인 반탄화공정을 위한 질량감소모델을 제시 하고자한다. 승온 속도(heating rate)를 $7.5^{\circ}C/min$, $15^{\circ}C/min$, $22.5^{\circ}C/min$의 조건에서의 열중량분석 결과를 토대로 속도모델식(Arrhenius method, Ingraham & Marrier method 등)을 적용하여, 반응속도상수를 도출하였다. 이 반응속도상수를 이용하여 질량감소 모델을 정립하였고, 이를 실험결과와 비교, 검증하였다.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.16 no.3
• /
• pp.217-225
• /
• 2013

It is time to develop new renewable energy that could fundamentally replace fossil fuel, which has been increasingly needed due to environmental pollution and energy security. Korean marine bio-energy development project is planned to produce 50% of total bioenergy. This study attempts to measure the greenhouse gas emission reduction benefits of marine bio-energy development project through contingent valuation method. Single bounded dichotomous choice (SBDC) is applied with spike model. The results show that the average willingness to pay are estimated to be KRW 4,190 at SBDC, per household per year. If the result has been expanded to the region which is survey conducted, KRW 50.1 billion annually. These quantitative information can be usefully utilized in the cost benefit analysis to implement project and policy-making for the industrialization of marine bio-energy development project.