• Journal of the Korean Crystal Growth and Crystal Technology
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• v.22 no.3
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• pp.115-121
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• 2012

Sapphire single crystals have been highlighted for epitaxial gallium nitride films in high-power laser and light emitting diode (LED) industries. Among the many crystal growth methods, the Kyropoulos process is an excellent commercial method for growing larger, high-optical-quality sapphire crystals with fewer defects. Because the properties and growth behavior of sapphire crystals are influenced largely by the temperature distribution and convection of molten sapphire during the manufacturing process, accurate predictions of the thermal fields and melt flow behavior are essential to design and optimize the Kyropoulos crystal growth process. In this study, computational fluid dynamic simulations were performed to examine the effects of the crucible geometry aspect ratio on melt convection during Kyropoulos sapphire crystal growth. The results through the evolution of various growth parameters on the temperature and velocity fields and convexity of the crystallization interface based on finite volume element simulations show that lower aspect ratio of the crucible geometry can be helpful for the quality of sapphire single crystal.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1087-1095
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• 2016

The study aims to analyze factors of box office utilizing big data. The film industry has been increasing in the scale, but the discussion on analysis and prediction of box-office hit has not secured reliability because of failing in including all relevant data. 13 films have sold 10 million tickets until the present in Korea. The study demonstrated laughs and tears as an main interior factors of box-office hit films which showed more than 10 milling tickets power. First, the study collected terms relevant to laugh and tear. Next, it schematizes how frequently laugh and tear factors could be found along the 5-film-stage (exposition - Rising action - crisis - climax - ending) and revealed box-office hit films by genre. The results of the analysis would contribute to the construction of comprehensive database for the box office predictions on future scenarios.

• Journal of Animal Science and Technology
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• v.57 no.12
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• pp.44.1-44.9
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• 2015

Background: Heat shock proteins play an important role in protection from stress stimuli and metabolic insults in almost all organisms. Methods: In this study, computational tools were used to deeply analyse the physicochemical characteristics and, using homology modelling, reliably predict the tertiary structure of the blunt snout bream (Ma-) Hsp70 and Hsc70 proteins. Derived three-dimensional models were then used to predict the function of the proteins. Results: Previously published predictions regarding the protein length, molecular weight, theoretical isoelectric point and total number of positive and negative residues were corroborated. Among the new findings are: the extinction coefficient (33725/33350 and 35090/34840 - Ma-Hsp70/ Ma-Hsc70, respectively), instability index (33.68/35.56 - both stable), aliphatic index (83.44/80.23 - both very stable), half-life estimates (both relatively stable), grand average of hydropathicity (-0.431/-0.473 - both hydrophilic) and amino acid composition (alanine-lysine-glycine/glycine-lysine-aspartic acid were the most abundant, no disulphide bonds, the N-terminal of both proteins was methionine). Homology modelling was performed by SWISS-MODEL program and the proposed model was evaluated as highly reliable based on PROCHECK's Ramachandran plot, ERRAT, PROVE, Verify 3D, ProQ and ProSA analyses. Conclusions: The research revealed a high structural similarity to Hsp70 and Hsc70 proteins from several taxonomically distant animal species, corroborating a remarkably high level of evolutionary conservation among the members of this protein family. Functional annotation based on structural similarity provides a reliable additional indirect evidence for a high level of functional conservation of these two genes/proteins in blunt snout bream, but it is not sensitive enough to functionally distinguish the two isoforms.

• Nuclear Engineering and Technology
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• v.45 no.7
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• pp.827-838
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• 2013

Interaction layer growth between U-Mo alloy fuel particles and Al in a dispersion fuel is a concern due to the volume expansion and other unfavorable irradiation behavior of the interaction product. To reduce interaction layer (IL) growth, a small amount of Si is added to the Al. As a result, IL growth is affected by the Si content in the Al matrix. In order to predict IL growth during fabrication and irradiation, empirical models were developed. For IL growth prediction during fabrication and any follow-on heating process before irradiation, out-of-pile heating test data were used to develop kinetic correlations. Two out-of-pile correlations, one for the pure Al matrix and the other for the Al matrix with Si addition, respectively, were developed, which are Arrhenius equations that include temperature and time. For IL growth predictions during irradiation, the out-of-pile correlations were modified to include a fission-rate term to consider fission enhanced diffusion, and multiplication factors to incorporate the Si addition effect and the effect of the Mo content. The in-pile correlation is applicable for a pure Al matrix and an Al matrix with the Si content up to 8 wt%, for fuel temperatures up to $200^{\circ}C$, and for Mo content in the range of 6 - 10wt%. In order to cover these ranges, in-pile data were included in modeling from various tests, such as the US RERTR-4, -5, -6, -7 and -9 tests and Korea's KOMO-4 test, that were designed to systematically examine the effects of the fission rate, temperature, Si content in Al matrix, and Mo content in U-Mo particles. A model converting the IL thickness to the IL volume fraction in the meat was also developed.

• Journal of Environmental Health Sciences
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• v.45 no.2
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• pp.173-185
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• 2019

Objectives: The objectives of this study are to evaluate the accuracy and precision of exposure model ECETOC TRA v.3.1 by comparing model predictions with repeated exposure measurements in Korean workplaces and to investigate the applicability of ECETOC TRA to Korean workplace exposure assessment in K-REACH. Methods: Measured values and work conditions for 14 kinds of chemicals collected from exposure field surveys conducted at 10 companies in Korea were utilized for this study. All possible process categories (PROCs) considered to be relevant to each work process classification were selected and applied to ECETOC TRA as major determining parameters. In order to quantify the accuracy of the model, the lack of agreement (bias, relative bias, precision) was calculated and the risk ratios for each exposure situation between estimated and measured were also compared. Results: The estimated values varied between five and 25 times according to the PROCs for all exposure situations (ESs) based on tasks/chemicals. The results showed that most of the estimated values were below the measured values, and just 13 of 53 tasks were above the measured values. The overall bias and precision were $-2.91{\pm}1.62$ with ECETOC TRA, and we found that ECETOC TRA showed a low level of conservatism when applied to Korean workplaces, similar to previous studies. Conclusions: This study demonstrates that the existed PROC codes have limitations in fully covering various ESs in Korea. In order to improve the applicability of ECETOC TRA in K-REACH, the addition of new PROCs for Korean industries are necessary.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.1
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• pp.111-122
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• 2014

The provided habitat of many services from natural capital is important. But because most ecosystem services tools qualitatively evaluated biodiversity or habitat quality, this study quantitatively analyzed those aspects using the species distribution model (MaxEnt). This study used location point data of the goat(Naemorhedus caudatus), marten(Martes flavigula), leopard cat(Prionailurus bengalensis), flying squirrel(Pteromys volans aluco) and otter(Lutra lutra) from the 3rd National Ecosystem Survey. Input data utilized DEM, landcover classification maps, Forest-types map and digital topographic maps. This study generated the MaxEnt model, randomly setting 70% of the presences as training data, with the remaining 30% used as test data, and ran five cross-validated replicates for each model. The threshold indicating maximum training sensitivity plus specificity was considered as a more robust approach, so this study used it to conduct the distribution into presence(1)-absence(0) predictions and totalled up a value of 5 times for uncertainty reduction. The test data's ROC curve of endangered mammals was as follows: growing down goat(0.896), otter(0.857), flying squirrel(0.738), marten(0.725), and leopard cat(0.629). This study was divided into two groups based on habitat: the first group consisted of the goat, marten, leopard cat and flying squirrel in the forest; and the second group consisted of the otter in the river. More than 60 percent of endangered mammals' distribution probability were 56.9% in the forest and 12.7% in the river. A future study is needed to conduct other species' distribution modeling exclusive of mammals and to develop a collection method of field survey data.

• Information Systems Review
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• v.26 no.2
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• pp.83-93
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• 2024

This study proposes a preprocessing methodology based on Dynamic Time Warping (DTW) and k-Nearest Neighbors (kNN) to effectively represent time series data for predicting the completion quality of electroplating baths. The proposed DTW-based kNN preprocessing approach was applied to various regression models and compared. The results demonstrated a performance improvement of up to 43% in maximum RMSE and 24% in MAE compared to traditional decision tree models. Notably, when integrated with neural network-based regression models, the performance improvements were pronounced. The combined structure of the proposed preprocessing method and regression models appears suitable for situations with long time series data and limited data samples, reducing the risk of overfitting and enabling reasonable predictions even with scarce data. However, as the number of data samples increases, the computational load of the DTW and kNN algorithms also increases, indicating a need for future research to improve computational efficiency.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.807-814
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• 2021

As economic activities decrease, and the stock market decline due to COVID-19, many people are jumping into stock investment as an alternative source of income. As people's interest increases, many stock price analysis studies are underway to earn more profits. Due to the variance observed in the stock markets, it is necessary to analyze each stock independently and consistently. To solve this problem, we designed and implemented models and services that analyze stock prices using a reinforcement learning technique called Asynchronous Advantage Actor-Critic(A3C). Stock market data reflected external factors such as government bonds and KOSPI (Korea Composite Stock Price Index) as well as stock prices. Our proposed work provides a web service with a visual representation of predictions of stocks and stock information through which directions are given to investors to make safe investments without analyzing domestic and foreign stock market trends.

• Journal of the Korean Society for Nondestructive Testing
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• v.18 no.6
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• pp.445-454
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• 1998

In order to establish a technical concept for the detection of defects in weldments in thin steel plate, an experimental and theoretical investigation was carried out for artificial defects in a steel plate having a thickness of 2.4mm by using the guided wave technique. In particular the goal was to find the most effective testing parameters paying attention to the relationship between the excitation frequency by a tone burst system and various incident angles. It was found that the test conditions that worked best was for a frequency of 840kHz and an incident angle of 30 or 85 degrees, most of the defects were detected with these conditions. Also, it was clear that a guided wave mode generated under an incident angle of 30 degrees was a symmetric mode, So, and that of 85 degrees corresponded to an antisymmetric mode, Ao. By using the two modes, most of all of the defects could be detected. Furthermore, it was shown that the antisymmetric mode was more sensitive to defects near the surface than the symmetric mode. Theoretical predictions confirmed this sensitivity improvement with Ao for surface defects because of wave structure variation and energy concentration near the surface.

• Computers and Concrete
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• v.20 no.6
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• pp.635-643
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• 2017

The rehabilitation and strengthening of concrete structures using Fiber-Reinforced Polymer (FRP) materials have been widely investigated. As a priority issue, however, the effect of curing conditions on the bonding behavior between FRP and concrete structures is still elusive. This study aims at developing a prediction model to accurately capture the mode-II interfacial debonding between FRP strips and concrete under different curing conditions. Single shear debonding experiments were conducted on FRP-concrete samples with respect to different curing time t and temperatures T. The J-integral formulation and constrained least square minimization are carried out to calibrate the parameters, i.e., the maximum slip $\bar{s}$ and stretch factor n. The prediction model is developed based on the cohesive model and Arrhenius relationship. The experimental data are then analyzed using the proposed model to predict the debonding between FRP and concrete, i.e., the interfacial shear stress-slip relationship. A Finite Element (FE) model is developed to validate the theoretical predictions. Satisfactory agreements are obtained. The prediction model can be used to accurately capture the bonding performance of FRP-concrete structures.