• Journal of Korean Society of Steel Construction
• /
• v.20 no.1
• /
• pp.151-163
• /
• 2008

A formulation of three-dimensional model of articulated train-b ridge dynamic interaction has been made for the Korean eXpress Train (KTX). Semi-periodic profiles of rail irregularities consisting of elevation, alignment, cross and gauge irregularities have also been proposed using FRA maximum tolerable rail deviations. The effects of rail joints and sleeper step were also included. The resulting system matrices of train and bridge are very spare, and thus, are stored in one-dimensional arrays, yielding a time-efficient solution. A numerical algorithm for computing bridge-train response including an iterative scheme is also formulated. A program simulating train-bridge interaction and solving this problem using the new algorithm is implemented as new modules for the f inite element analysis software named XFINAS. Computed results using the new program are then checked by that of the validated 2-D bridge-train interaction model. This new 3D analysis provides more detailed train responses such as swaying, bouncing, rolling, pitching and yawing accelerations, which are useful inevaluating passenger riding comfort. Train operation safety and derailment could also be directly investigated by relative wheel displacements computed from this program.

• Korean Journal of Plant Taxonomy
• /
• v.46 no.4
• /
• pp.361-370
• /
• 2016

An area comprising Juwangsan National Park and its adjacent mountains (southeastern Korean Peninsula) is a good model system for testing the effects of physical barriers to gene flows in plant populations. We predicted that plant species consisting of isolated populations are genetically more differentiated than those that are rather continuously distributed. Most populations of Sedum polytrichoides occur in four isolated valleys, and we assessed the genetic variability and structures using twelve allozyme loci in ten populations. We also compared the present results to earlier findings pertaining to the two co-occurring herbs Hylotelephium ussuriense (${\equiv}$ Sedum ussuriense) (growing only in the four isolated valleys) and S. kamtschaticum (rather continuously distributed). We found moderate levels of within-population genetic variation in S. polytrichoides ($H_{e}=0.112$). Estimates of among-population divergence in S. polytrichoides were also moderate ($F_{ST}=0.250$) and, as expected, very similar to that of H. ussuriense (0.261) but considerably higher than the variation in S. kamtschaticum (0.165). An analysis of molecular variance (AMOVA) revealed that S. polytrichoides and H. ussuriense had higher percentages of among-valley variation (19% each) than S. kamtschaticum (4%). Most of this variation, as also indicated by the STRUCTURE program, was due to differences in genetic profiles between the two central valleys. We concluded that the genetic differences observed between species (S. kamtschaticum vs. S. polytrichoides and H. ussuriense) are mainly due to differences in their distribution within the study area.

• Journal of the Korea Convergence Society
• /
• v.12 no.10
• /
• pp.177-188
• /
• 2021

In South Korea, with the advancement of the 'Port' project, the regeneration industry adapted to the modern economic development has been promoted, leading to construction around the port was also redefined. Therefore, through regeneration, the problem of image construction of buildings around the port has been re-examined, in which color is an important content of image construction. In this study, the exterior walls of abandoned factory buildings in the port area of Bongnaedong, Pusan were selected as the color research object and evaluated according to the characteristics of the regenerated factory buildings combined with the building color function. Technically, KSCP color analysis system is used for color analysis. In this way, the color plan for the exterior walls of the factory buildings is proposed to visually enhance the image of abandoned factory buildings and attract more attention, thus driving the regional economic development. The results of this study show that in order to adapt to the regional, industrial and commercial characteristics of the regenerated port space, the color hue, lightness, chroma and use area of the building can be changed to enhance the aesthetic value and enhance the inductivity and security.

• Journal of Technology Innovation
• /
• v.29 no.4
• /
• pp.1-30
• /
• 2021

Due to the recent development of system semiconductors, technical innovation for the electric devices of the automobile industry is rapidly progressing. In particular, the electric device of automobiles is accelerating technology development competition among automobile parts makers, and the development cycle is also changing rapidly. Due to these changes, the importance of strategic planning for R&D is further strengthened. Due to the paradigm shift in the automobile industry, the Product-Technical Roadmap (P/TRM), one of the R&D strategies, analyzes technology forecasting, technology level evaluation, and technology acquisition method (Make/Collaborate/Buy) at the planning stage. The product-technical roadmap is a tool that identifies customer needs of products and technologies, selects technologies and sets development directions. However, most companies are developing the product-technical roadmap through a qualitative method that mainly relies on the technical papers, patent analysis, and expert Delphi method. In this study, empirical research was conducted through simulations that can supplement and strengthen the product-technical roadmap centered on the automobile industry by fusing Gartner's hype cycle, cumulative moving average-based data preprocessing, and deep learning (LSTM) time series analysis techniques. The empirical study presented in this paper can be used not only in the automobile industry but also in other manufacturing fields in general. In addition, from the corporate point of view, it is considered that it will become a foundation for moving forward as a leading company by providing products to the market in a timely manner through a more accurate product-technical roadmap, breaking away from the roadmap preparation method that has relied on qualitative methods.

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

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.39 no.1
• /
• pp.165-174
• /
• 2019

As a nonstationarity is observed in hydrological data, various studies on nonstationary frequency analysis for hydraulic structure design have been actively conducted. Although the inherent diversity in the atmosphere-ocean system is known to be related to the nonstationary phenomena, a nonstationary frequency analysis is generally performed based on the linear trend. In this study, a nonstationary frequency analysis was performed using climate indices as covariates to consider the climate variability and the long-term trend of the extreme rainfall. For 11 weather stations where the trend was detected, the long-term trend within the annual maximum rainfall data was extracted using the ensemble empirical mode decomposition. Then the correlation between the extracted data and various climate indices was analyzed. As a result, autumn-averaged AMM, autumn-averaged AMO, and summer-averaged NINO4 in the previous year significantly influenced the long-term trend of the annual maximum rainfall data at almost all stations. The selected seasonal climate indices were applied to the generalized extreme value (GEV) model and the best model was selected using the AIC. Using the model diagnosis for the selected model and the nonstationary GEV model with the linear trend, we identified that the selected model could compensate the underestimation of the rainfall quantiles.

• The Journal of Society for e-Business Studies
• /
• v.24 no.1
• /
• pp.1-16
• /
• 2019

Recently, since responding to meteorological changes depending on increasing greenhouse gas and electricity demand, the importance prediction of photovoltaic power (PV) is rapidly increasing. In particular, the prediction of PV power generation may help to determine a reasonable price of electricity, and solve the problem addressed such as a system stability and electricity production balance. However, since the dynamic changes of meteorological values such as solar radiation, cloudiness, and temperature, and seasonal changes, the accurate long-term PV power prediction is significantly challenging. Therefore, in this paper, we propose PV power prediction model based on deep learning that can be improved the PV power prediction performance by learning to use meteorological and seasonal information. We evaluate the performances using the proposed model compared to seasonal ARIMA (S-ARIMA) model, which is one of the typical time series methods, and ANN model, which is one hidden layer. As the experiment results using real-world dataset, the proposed model shows the best performance. It means that the proposed model shows positive impact on improving the PV power forecast performance.

• The Korean Journal of Archival Studies
• /
• no.54
• /
• pp.81-109
• /
• 2017

This study suggests an analysis of the reviews provided by international archival professionals on the RiC-CM draft published by ICA EGAD. Some implications for the Korean archival management environment were also suggested. Some professional reviews were accessible through the internet. Italian archival professionals held workshops at various levels for the analysis and discussion of the draft. Duranti, the project director of InterPARES, also gave opinions about the draft in cluding the perspective of digital preservation. In the review of Artefactual, the draft was discussed in terms of system implementation. Reed, the director of Recordkeeping Innovation, also gave a feedback based on the record management experiences in Australia. Some implications can be suggested based on these professional opinions. First, we should try to build a test bed for the adoption of RiC to archival description in the Korean environment. Second, a minimum level of data elements that can secure authenticity and integrity will also be needed. Third and lastly, rich authority data for agents and functions related to archival records and records groups are essential to take full advantage of the standard.

• Journal of the Korean Crystal Growth and Crystal Technology
• /
• v.29 no.2
• /
• pp.71-76
• /
• 2019

Recently, the demand of labels for product management is increasing, as the automation system becomes more common. the development of functional labels which can be used in various environments has been rapidly proceeded. In the case of a printed circuit board, barcode labels with thermal and chemical stability are generally used due to a high temperature process around $300^{\circ}C$ and chemical cleaning in the manufacturing process. However, the yellowing phenomenon of labels that can lower the resolution of printed barcode image still needs to be prevented. In this study, we prepared a composite coating layer using a silica inorganic binder and a titanium dioxide white pigment, and developed a functional labels with thermal and chemical stability. The silica inorganic binder prepared by sol-gel process was confirmed to show excellent adhesion and abrasion resistance with the polyimide film. The white coating layer could be formed on the polyimide film with mixing the silica inorganic binder and titanium dioxide white pigment. The prepared coating layer showed excellent whiteness and glossiness above $400^{\circ}C$. The excellent chemical stability of the coating layer was also confirmed by the chemical treatment with acidic (pH 1.6) and basic (pH 13.6) cleaners.

• Journal of the Korean GEO-environmental Society
• /
• v.12 no.10
• /
• pp.39-49
• /
• 2011

Recently PBD method, one of acceleration of consolidation methods is used in the soft ground to shorten consolidation time for fast settlement during construction. It is economical and easy to work. Discharge capacity of PBD is sensitive in proportion to thickness of soft ground layer, and drainage of PBD declines due to disturbance effect in surrounding ground by mandrel used for vertical drainage setting and setting machines and type. Also, deviation of discharge capacity is large according to ground condition, construction condition and soil properties. In addition, when embankment loading is not conducted instantly after PBD setting due to rain or lack of embankment material supply, it causes leaving period problems. But cause and analysis of those problems for discharge capacity is lack. So, in this test, ground improvement and discharge capacity is investigated by implementing composite discharge capacity test for analysis of an effect factor of PBD discharge capacity with leaving period. After fixing the vertical drain on a cylindrical cylinder, put churned sample into the cylinder. Then leave 0day, 30day, 60day and 90day. And then, load following the loading step of 30, 70 and 120kPa using a pressure device. As a result, the longer leaving period, discharge capacity is reduced. It is caused by a decrease of discharge area caused by creep transformation moisture absorption of PBD filter after long leaving period.