• Science of Emotion and Sensibility
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• v.15 no.4
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• pp.503-516
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• 2012

According to the researches of robot and software agent until now, computational emotion model is dependent on system, so it is hard task that emotion models is separated from existing systems and then recycled into new systems. Therefore, I introduce the Engine of computational Emotion model (shall hereafter appear as EE) to integrate with any robots or agents. This is the engine, ie a software for independent form from inputs and outputs, so the EE is Emotion Generation to control only generation and processing of emotions without both phases of Inputs(Perception) and Outputs(Expression). The EE can be interfaced with any inputs and outputs, and produce emotions from not only emotion itself but also personality and emotions of person. In addition, the EE can be existed in any robot or agent by a kind of software library, or be used as a separate system to communicate. In EE, emotions is the Primary Emotions, ie Joy, Surprise, Disgust, Fear, Sadness, and Anger. It is vector that consist of string and coefficient about emotion, and EE receives this vectors from input interface and then sends its to output interface. In EE, each emotions are connected to lists of emotional experiences, and the lists consisted of string and coefficient of each emotional experiences are used to generate and process emotional states. The emotional experiences are consisted of emotion vocabulary understanding various emotional experiences of human. This study EE is available to use to make interaction products to response the appropriate reaction of human emotions. The significance of the study is on development of a system to induce that person feel that product has your sympathy. Therefore, the EE can help give an efficient service of emotional sympathy to products of HRI, HCI area.

• Journal of IKEEE
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• v.22 no.3
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• pp.822-828
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• 2018

Recently, energy issues such as massive blackout due to increase in power consumption have been emerged, and it is necessary to improve the accuracy of prediction of power consumption as a solution for these problems. In this study, we investigate the difference between the actual power consumption and the predicted power consumption through the deep learning- based power consumption forecasting experiment, and the possibility of adjusting the power reserve ratio. In this paper, the prediction of the power consumption based on the deep learning can be used as a basis to reduce the power reserve ratio so as not to excessively produce extra power. The deep learning method used in this paper uses a learning model of long-short-term-memory (LSTM) structure that processes time series data. In the computer simulation, the generated power consumption data was learned, and the power consumption was predicted based on the learned model. We calculate the error between the actual and predicted power consumption amount, resulting in an error rate of 21.37%. Considering the recent power reserve ratio of 45.9%, it is possible to reduce the reserve ratio by 20% when applying the power consumption prediction algorithm proposed in this study.

• Korean Chemical Engineering Research
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• v.53 no.2
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• pp.150-155
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• 2015

Recently, LNG receiving terminals have been widely constructed and expanded for an increase in LNG demand. Selection of the storage tank for send-out and estimation of send-out flow rate have significant influence to process operation and economics. In this study, a send-out flow rate of each storage tank is optimized in order to minimize the total BOG generation rate. Considering a size and characteristic of each storage tanks, BOG flow rates are estimated using a dynamic simulation with varying liquid levels in the tanks. The regression model is developed fitting BOG flow rates and tank liquid levels, which are boil off rate model to predict BOG flow rates with particular level data. The objective function and constraints including required total send-out flow rate and level limit in the tanks are formulated to optimize a send-out flow rate of each tank. This method for optimization of send-out operation is applied to the Incheon LNG receiving terminal considering two scenarios for various liquid levels and maximum and minimum required send-out flow rates. For maximum required send-out flow rate, this method achieves BOG reduction of 9% comparing with assumed conventional operation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.3
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• pp.197-205
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• 2020

Korean language has the characteristics that the pronunciation of phoneme units such as vowels and consonants are fixed and the pronunciation associated with a notation does not change, so that foreign learners can approach rather easily Korean language. However, when one pronounces words, phrases, or sentences, the pronunciation changes in a manner of a wide variation and complexity at the boundaries of syllables, and the association of notation and pronunciation does not hold any more. Consequently, it is very difficult for foreign learners to study Korean standard pronunciations. Despite these difficulties, it is believed that systematic analysis of pronunciation errors for Korean words is possible according to the advantageous observations that the relationship between Korean notations and pronunciations can be described as a set of firm rules without exceptions unlike other languages including English. In this paper, we propose a visualization framework which shows the differences between standard pronunciations and erratic ones as quantitative measures on the computer screen. Previous researches only show color representation and 3D graphics of speech properties, or an animated view of changing shapes of lips and mouth cavity. Moreover, the features used in the analysis are only point data such as the average of a speech range. In this study, we propose a method which can directly use the time-series data instead of using summary or distorted data. This was realized by using the deep learning-based technique which combines Self-organizing map, variational autoencoder model, and Markov model, and we achieved a superior performance enhancement compared to the method using the point-based data.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.10 no.1
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• pp.100-112
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• 2005

Soil temperature was measured from the surface to 40 cm depth at three stations with different heights in tidal flat of Gomso Bay, west coast of Korea, for one month in every season 2004 to examine the thermal structure and the variation. Mean temperature in surface layer was higher in summer and lower in winter than in lower layer, reflecting the seasonal variation of vertically propagating structure of temperature by heating and cooling from the tidal flat surface. Standard deviation of temperature decreased from the surface to lower layer. Periodic variations of solar radiation energy and tide mainly caused short term variation of soil temperature, which was also intermittently influenced by precipitation and wind. Time series analysis showed the power spectral energy peaks at the periods of 24, 12 and 8 hours, and the strongest peak appeared at 24 hour period. These peaks can be interpreted as temperature waves forced by variations of solar radiation, diurnal tide and interaction of both variations, respectively. EOF analysis showed that the first and the second modes resolved 96% of variation of vertical temperature structure. The first mode was interpreted as the heating antl cooling from tidal flat surface and the second mode as the effect of phase lag produced by temperature wave propagation in the soil. The phase of heat transfer by 24 hour period wave, analyzed by cross spectrum, showed that mean phase difference of the temperature wave increased almost linearly with the soil depth. The time lags by the phase difference from surface to 10, 20 and 40cm were 3.2,6.5 and 9.8 hours, respectively. Vertical thermal diffusivity of temperature wave of 24 hour period was estimated using one dimensional thermal diffusion model. Average diffusivity over the soil depths and seasons resulted in $0.70{\times}10^{-6}m^2/s$ at the middle station and $0.57{\times}10^{-6}m^2/s$ at the lowest station. The depth-averaged diffusivity was large in spring and small in summer and the seasonal mean diffusivity vertically increased from 2 cm to 10 cm and decreased from 10 cm to 40 cm. Thermal propagation speeds were estimated by $8.75{\times}10^{-4}cm/s,\;3.8{\times}10{-4}cm/s,\;and\;1.7{\times}10^{-4}cm/s$ from 2 cm to 10 cm, 20 cm and 40 cm, respectively, indicating the speed reduction with depth increasing from the surface.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.8
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• pp.1007-1013
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• 2013

This study aims to analyze the aerodynamics when the geometry of the turbine rotor is modified. The turbine used in this study is a small engine used in the APU of a helicopter. It is difficult to improve the performance of small engines owing to the structural weakness of the blade tip. Therefore, the improvement of the hub geometry is investigated in many ways. The working fluid of a turbine is a high-temperature and high-pressure gas. The heat transfer rate of the turbine surface should be considered to avoid the destruction of blade owing to the heat load. The SST turbulence model gives an excellent prediction of the aerodynamic behavior and heat transfer characteristics when the numerical simulations are compared with the experimental results. In conclusion, the aerodynamic efficiency is improved when a bulbous design is applied to the leading edge near the hub. The endwall loss is reduced by 15%.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.622-628
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• 2020

This paper proposes a music generation technique that automatically generates trot music using a Generative Adversarial Network (GAN) model composed of a Recurrent Neural Network (RNN). The proposed method uses a method of creating a chord as a skeleton of the music, creating a melody and bass in stages based on the chord progression made, and attaching it to the corresponding chord to complete the structured piece. Also, a new chorus chord progression is created from the verse chord progression by applying the characteristics of a trot song that repeats the structure divided into an individual section, such as intro, verse, and chorus. And it extends the length of the created trot. The quality of the generated music was specified using subjective evaluation and objective evaluation methods. It was confirmed that the generated music has similar characteristics to the existing trot.

• The Journal of Korean Association of Computer Education
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• v.7 no.6
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• pp.1-12
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• 2004

Current computer education is difficult to educate basic concepts and principals of the computer science because the 7th curriculum of computer education is focused on the application of software. According to the ACM K-12 report about the computer science education model, current computer education is taking the wrong way and we should put the highly priority on the education of the fundamentals through programming languages for a better computer education oriented to the computer science. This paper introduces a new object-oriented educational programming language "Dolittle". The design principals of Dolittle are simple syntax of Korean, incremental programming, text based programming, aliasing of function, and object-oriented programming. Being applied to middle school classes, we can confirm that Dolittle is easy to learn, and gives rise to high interest and keeps interest through a course, and also is of great practical use in class for programming novice.

• Korean Journal of Optics and Photonics
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• v.13 no.1
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• pp.1-8
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• 2002

Optical payloads for earth-observation satellites become bigger as the required resolution becomes finer. For example, the diameter of the primary mirror of IKONOS, which has ground sampling distances of 1m/4m in panchromatic/multi spectral bands, is about 700mm. As the size of optical payload becomes bigger, the light-weighting of the mirrors becomes more significant. This paper presents the FEM results of the following four mirror types of 300 m diameter under gravity release and temperature changes: flat back mirror, single arch mirror, double arch mirror, and honeycomb sandwich mirror. Furthermore, this paper extends the FEM results to larger mirrors up to the diameter of 1m based on a general scaling law and Valenete\`s equation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.3
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• pp.479-486
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• 2002

In this study, the progressive inelastic deformation, so called, thermal ratchet phenomenon which can occur in high temperature structures of liquid metal reactor was simulated with thermal ratchet structural test facility and 316L stainless steel test cylinder. The thermal ratchet deformation at the reactor baffle cylinder of the liquid metal reactor can occur due to the moving temperature distribution along the axial direction as the sodium free surface moves up and down under the cyclic heat-up and cool-down transients. The ratchet deformation was measured with the laser displacement sensor and LVDTs after cooling the structural specimen which is heated up to 55$0^{\circ}C$ with steep temperature gradients along the axial direction. The temperature distribution of the test cylinder along the axial direction was measured with 28 channels of thermocouples and was used for the ratchet analysis. The thermal ratchet deformation was analyzed with the constitutive equation of nonlinear combined hardening model which was implemented as ABAQUS user subroutine and the analysis results were compared with those of the test. Thermal ratchet load was applied 9 times and the residual displacement after 9 cycles of thermal load was measured to be 1.79mm. The ratcheting deformation shapes obtained by the analysis with the combined hardening model were in reasonable agreement with those of the structural tests.