• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.3
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• pp.202-208
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• 2001

Under the constant daylength of 13 hours and growth temperatures of 15$^{\circ}C$ to 27$^{\circ}C$, the final number of loaves (FNL) on the main culm was constant as 15 regardless of temperature in rice variety 'Kwanganbyeo'. Leaf appearance rate (LAR) increased with rising temperature and decreased with phenological development. Threshold temperature (T$_{o}$) was not constant across growth stages, but increased with phenological development. Effective accumulated temperature (EAT), which is calculated by the summation of values subtracting T0 from daily mean temperature, is closely related with number of leaves appeared (LA). LA was fitted to bilinear, quadratic, power and logistic function of EAT. Among the functions, logistic function had the best fitness of which coefficient of determination was $R^2$=0.995. Therefore, LAR prediction model was established by differentiating this function in terms of time: (equation omitted). where dL/dt is LAR, T$_1$ is daily mean temperature, L is the number of leaves appeared, and a, b, and c are constants that were estimated as 41.8, 1098.38, and -0.9273, respectively. When predictions of LA were made by LAR prediction model using data independent of model establishment, the observed and predicted LA showed good agreement of $R^2$$\geq$0.99.

• Journal of Korea Multimedia Society
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• v.5 no.5
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• pp.512-522
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• 2002

In this paper, we propose a hybrid method which is mixed with frame selection and weighting model rank method, based on GMM(gaussian mixture model), for real-time text-independent speaker recognition system. In the system, maximum likelihood estimation was used for GMM parameter optimization, and maximum likelihood was used for recognition basically Proposed hybrid method has two steps. First, likelihood score was calculated with speaker models and test data at frame level, and the difference is calculated between the biggest likelihood value and second. And then, the frame is selected if the difference is bigger than threshold. The second, instead of calculated likelihood, weighting value is used for calculating total score at each selected frame. Cepstrum coefficient and regressive coefficient were used as feature parameters, and the database for test and training consists of several data which are collected at different time, and data for experience are selected randomly In experiments, we applied each method to baseline system, and tested. In speaker recognition experiments, proposed hybrid method has an average of 4% higher recognition accuracy than frame selection method and 1% higher than W method, implying the effectiveness of it.

• Korean Journal of Cognitive Science
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• v.31 no.1
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• pp.1-23
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• 2020

This paper introduces SNUDM, an analysis program for Ratcliff's diffusion model, which has been one of the most important models in cognitive psychology over the past 35 years and which has come to occupy an important place in cognitive neuroscience in recent years. The analysis tool is designed with the basic principles of easy comprehension and simplicity in use. A diffusion process was programmed as the limit of a simple random walk in a manner resembling Ratcliff & Tuerlinckx(2002). The response time distribution of the model was constructed by simulating the time taken by a random walk until it reaches a threshold with small steps. The optimal parameter values in the model are found to be the smallest value of the chi-square values obtained by comparing the resulting distribution and the experimental data using Simplex method. For simplicity and ease of use, the input file used here is created as a file containing the quantile of the reaction time, the trials and other information. The number of participants and the number of conditions required for such work programs are given in a way that answers the question. Using this analysis tool, the experimental data of Ratcliff, Gomez, & McKoon(2004) were analyzed. We found the very similar pattern of parameter values to Ratcliff et al.(2004) found. When comparing DMAT, fast-dm and SNUDM with the generated data, we found that when the number of trials is small, SNUDM estimates the boundary parameter to a value similar to fast-dm and less than the DMAT. In addition, when the number of trials was large, it was confirmed that all three tools estimate parameters similarly.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.76-91
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• 2019

There have been many studies to examine the patterns in innovations reflecting industry-specific characteristics from an evolutionary economics perspective. The purpose of this study is to identify industry-specific differences in product innovation patterns and determinants of innovation performance. For this, Korean manufacturing is classified into high-tech industries and low-tech industries according to technology intensity. It is also pointed out that existing research does not reflect the decision-making process of firms' R&D implementations. In order to solve this problem, this study presents a Heckman sample selection model and a double-hurdle model as alternatives, and analyzes data from 1,637 firms in the 2014 Survey on Technology of SMEs. As a result, it was confirmed that the determinants and patterns of manufacturing in small and medium-size enterprise (SME) product innovation are significantly different between high-tech and low-tech industries. Also, through an extended empirical model, we found that there exist a sample selection bias and a hurdle-like threshold in the decision-making process. In this study, the industry-specific features and patterns of product innovation are examined from a multi-sided perspective, and it is meaningful that the decision-making process for manufacturing SMEs' R&D performance can be better understood.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.165-178
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• 2021

We studied driftwood behaviors including generation and deposition in a tsunami using a numerical simulation. We used an integrated two-dimensional numerical model, which included a driftwood dynamics model. The study area was Sendai, Japan. Observation data collected by Inagaki et al. (2012) were used to verify the simulation results by comparing them with driftwood deposition patterns. A simplified model was developed to consider the threshold of driftwood generation by the drag force of water flows. To consider the volume of driftwood generated, we estimated the total wood number in the study area using Google Earth. Therefore, we simulated more than 13,000 pieces of driftwood that were generated and transported inland from approximately 300,000 trees that were growing in the forest. The final distribution of the driftwood was similar to the observation data. The reproducibility of the generation and deposition patterns of driftwood showed good agreement in terms of longitudinal deposition pattern. In the future, a sensitivity analysis on driftwood parameters, such as the size of the wood, boundary conditions, and grid size, will be implemented to predict the travel patterns of driftwood. Such modeling will be a useful methodology for disaster prediction based on water flow and driftwood.

• International Area Studies Review
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• v.22 no.4
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• pp.3-18
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• 2018

In this study, I examined capital market shock reaction effects of 29 OECD countries with the past 24 years sample period consisting of daily stock market return using T-GARCH model focused on volatility feedback hypothesis. US daily stock market return is used as a unique independent variable in this model in consideration of its characteristics of biggest market share and as an origin country of Global Financial Crisis. As a result, France, Finland, and Mexico in order are shown to be the strongest countries in the aspect of return spillovers from US. Canada, Mexico, and France are shown to be the highest countries in the aspect of explanatory power of model. The degrees of shock reaction are proved to be higher in order in Germany, Chile, Switzerland, and Denmark and those of downside shock reaction are seen higher in order in Greece, Great Britain, Australia, and Japan. Canada and Mexico belonging to NAFTA are shown to be higher in the return spillover from US and in the model explanatory power, but they are shown to be lower in the impact of shock reaction, suggesting that regional distance effect or gravity theory cannot be applied to financial spillovers any longer. In the analysis of subsample period of Global Financial Crisis, north American three countries do not show any consistent results as in the full sample period but shock reaction in the European countries are shown to record stronger, suggesting that shocks from US in the Crisis Times are transferred mainly to European region.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.242-250
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• 2019

In this paper, we propose a method to predict the failure of industrial robot using Seq2Seq (Sequence to Sequence) model, which is a model for transforming time series data among Artificial Neural Network models. The proposed method uses the data of the joint current and angular value, which can be measured by the robot itself, without additional sensor for fault diagnosis. After preprocessing the measured data for the model to learn, the Seq2Seq model was trained to convert the current to angle. Abnormal degree for fault diagnosis uses RMSE (Root Mean Squared Error) during unit time between predicted angle and actual angle. The performance evaluation of the proposed method was performed using the test data measured under different conditions of normal and defective condition of the robot. When the Abnormal degree exceed the threshold, it was classified as a fault, and the accuracy of the fault diagnosis was 96.67% from the experiment. The proposed method has the merit that it can perform fault prediction without additional sensor, and it has been confirmed from the experiment that high diagnostic performance and efficiency are available without requiring deep expert knowledge of the robot.

• Journal of Korea Water Resources Association
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• v.52 no.8
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• pp.515-529
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• 2019

Geospatial information for river network and watershed boundary have played a fundamental roles in terms of river management, planning and design, hydrological and hydraulic analysis. Irrespective of their importance, the lack of punctual update and improper maintenance in currently available river-related geospatial information systems has revealed inconsistency issues between individual systems and spatial inaccuracy with regard to reflecting dynamically transferring riverine geography. Given that digital elevation models (DEMs) of high spatial resolution enabling to reproduce precise river network are only available adjacent to national rivers, DEMs with poor spatial resolution lead to generate unreliable river network information and thereby reduce their extensible applicabilities. This study first of all evaluated published spatial information available in Korea with respect to their spatial accuracy and consistency, and also provides a methodology and tool to modify existing low resolution of DEMs by means of striation of conventional or digitized river network to replicate input river network in various degree of further delineation. The tool named FSND was designed to be operated in ArcGIS ModelBuilder which ensures to automatically simulate river network striation to DEMs and delineation with different flow accumulation threshold. The FNSD was successfully validated in Seom River basin to identify its replication of given river network manually digitized based on recent aerial photograph in conjunction with a DEM with 30 meter spatial resolution. With the derived accuracy of reproducibility, substantiation of a various order of river network and watershed boundary from the striated DEM posed tangible possibility for highly extending DEMs with low resolution to be capable of producing reliable riverine spatial information subsequently.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.3
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• pp.142-154
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• 2011

This study predicted the probability of corrosion initiation of reinforced concrete tunnel boxes structures using the Monte Carlo Simulation. For the inner wall and outer wall in the tunnel boxes, exposed to airborne chloride ion and seawater directly respectively, statistical values of parameters like diffusion coefficient D, surface chloride content $C_s$, cover depth c, and the chloride threshold level $C_{lim}$ were examined from experiment or literature review. Their average values accounted for $3.77{\times}10^{-12}m^2/s$, 3.0% by weight of cement, 94.7mm and 45.5mm for outer wall and inner wall, respectively, and 0.69% by weight of cement for D, $C_s$, c, and $C_{lim}$, respectively. With these parametric values, the distribution of chloride contents at rebar with time and the probability of corrosion initiation of the tunnel boxes, inner wall and outer wall, was examined by considering time dependency of chloride transport. From the examination, the histogram of chloride contents at rebar is closer to a gamma distribution, and the mean value increases with time, while the coefficient of variance decreases with time. It was found that the probability of corrosion initiation and the time to corrosion were dependent on the time dependency of chloride transport. Time independent model predicted time to corrosion initiation of inner wall and outer wall as 8 and 12 years, respectively, while 178 and 283 years of time to corrosion was calculated by time dependent model for inner wall and outer wall, respectively. For time independent model, the probability of corrosion at 100 years of exposure for inner wall and outer wall was ranged 59.5 and 95.5%, respectively, while time dependent model indicated 2.9 and 0.2% of the probability corrosion, respectively. Finally, impact of $C_{lim}$, including values specified in current codes, on the probability of corrosion initiation and corrosion free life is discussed.

• Korean journal of applied entomology
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• v.50 no.4
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• pp.373-378
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• 2011

The striped fruit fly, Bactrocera scutellata, damages pumpkin and other cucurbitaceous plants. The developmental period of each stage was measured at seven constant temperatures (15, 18, 21, 24, 27, 30, and $33{\pm}1.0^{\circ}C$). The developmental time of eggs ranged from 4.2 days at $15^{\circ}C$ to 0.9 days at $33^{\circ}C$. The developmental period of larvae was 4.2 days at $15^{\circ}C$, and slowed in temperatures above $27^{\circ}C$. The developmental period of pupa was 21.5 days at $15^{\circ}C$ and 7.6 days at $33^{\circ}C$. The mortality of eggs was 17.1% at $15^{\circ}C$ and 22.9% at $33^{\circ}C$, Larval mortalities (1st, 2nd, 3rd) were 24.1, 27.3 and 18.2%, respectively, at $15^{\circ}C$, Pupal mortalities were 18.2% at $15^{\circ}C$ and 23.1% at $33^{\circ}C$. The relationship between developmental rate and temperature fit both a linear model and a nonlinear model. The lower threshold temperatures of eggs, larvae, and pupae were 12.5, 10.7, and $6.3^{\circ}C$, respectively, and threshold temperature of the total immature period was $8.5^{\circ}C$. The thermal constants required to complete the egg, larval, and pupal stages were 33.2, 118.3, and 181.2 DD, respectively. The distribution of each development stages was described by a 3-parameter Weibull function.