• Journal of Environmental Science International
• /
• v.19 no.2
• /
• pp.157-170
• /
• 2010

Air mass recirculation is a common characteristic in the coastal area as a result of the land-sea breeze circulation. This study simulates the recirculation of air mass over the Gwangyang Bay using WRF-FLEXPART and offers a basic information about the effective domain size that can reflect recirculation. For this purpose, WRF is set up four nested domains and three cases are selected. Subsequently FLEXPART is operated on the basis of WRF output. During the clear summer days with weak wind speed, particles that emitted from Yeosu national industrial complex and Gwangyang iron works flow into emission sources because of the land-sea breeze. When land-sea breeze is strengthen, the recirculation phenomena appears clearly. However particles aren't recirculated under weak synoptic condition. Also plume trajectory is analyzed and as a consequence, the smallest domain area have to be multiplied by 1.3 to understand recirculated dispersion pattern of particles.

• Spatial Information Research
• /
• v.2 no.2
• /
• pp.107-116
• /
• 1994

Choropleth map is a type of thematic maps in which areal units are shaded with a color or pattern that symbolizes some characteristic of the mapped unit. CMS was first developed to produce choropleth maps on ordinary microcomputer environments in 1988. Since then there have been significant technological developments and enhancements in user environments, which have affected the field of choropleth mapping systems posi¬tively. A new version of CMS was developed in accordance with these changes. CMS II requires an IBM PC, or compatible, with the minimum 640KB memory and VGA graphic board. It supports HP laser jet printers to output a high resolution map. The program can use Hangul letters for main menu, map title, and legend. And dBase file format (DEW) was implemented to exchange attribute files effectively.

• The Journal of the Acoustical Society of Korea
• /
• v.28 no.2E
• /
• pp.43-50
• /
• 2009

To get more natural synthetic speech generated by a Korean TTS (Text-To-Speech) system, we have to know all the possible prosodic rules in Korean spoken language. We should find out these rules from linguistic, phonetic information or from real speech. In general, all of these rules should be integrated into a prosody-generation algorithm in a TTS system. But this algorithm cannot cover up all the possible prosodic rules in a language and it is not perfect, so the naturalness of synthesized speech cannot be as good as we expect. ANNs (Artificial Neural Networks) can be trained to learn the prosodic rules in Korean spoken language. To train and test ANNs, we need to prepare the prosodic patterns of all the phonemic segments in a prosodic corpus. A prosodic corpus will include meaningful sentences to represent all the possible prosodic rules. Sentences in the corpus were made by picking up a series of words from the list of PB (phonetically Balanced) isolated words. These sentences in the corpus were read by speakers, recorded, and collected as a speech database. By analyzing recorded real speech, we can extract prosodic pattern about each phoneme, and assign them as target and test patterns for ANNs. ANNs can learn the prosody from natural speech and generate prosodic patterns of the central phonemic segment in phoneme strings as output response of ANNs when phoneme strings of a sentence are given to ANNs as input stimuli.

• Journal of Sensor Science and Technology
• /
• v.19 no.2
• /
• pp.149-154
• /
• 2010

Top of the alumina body which is made according to plan has been printed using a screen printer equipment in order to print an electrode pattern. The electrode is connected with the quartz crystal oscillator of the piezoelectricity method which has a piezoelectric characteristic. The pressure contact department has been experimented using three type of the teflon. The teflon is good for pressure delivery vector but it is bad restitution. So we devised the structure which inserts the metal in the teflon. Bottom of the module is connected with the signal processing department which is planned in advance and then has investigated to characteristic. Therefore we have got the best output-voltage and frequency characteristic follows in the pressure.

• Journal of the Korean Society for Precision Engineering
• /
• v.27 no.8
• /
• pp.91-97
• /
• 2010

Micro-abrasive Jet Machining is one of the new technology which enables micro-scale machining on the surface of high brittle materials. In this technology it is very important to fabricate a mask that prevents excessive abrasives not to machine un-intend surface. Our previous work introduced the micro-stereolithography technology for the mask fabrication. And is good to not only planar material but also for non-planar materials. But the technology requires a 3 dimensional mask CAD model which is perfectly matched with the surface topology of parent material as an input. Therefore there is strong need to develop an automated modeling technology which produce adequate 3D mask CAD model in fast and simple way. This paper introduces a fast and simple mask modeling algorithm which represents geometry of models in voxel. Input of the modeling system is 2D pattern image, 3D CAD model of parent material and machining parameters for Micro-abrasive Jet Machining. And the output is CAD model of 3D mask which reflects machining parameters and geometry of the parent material. Finally the suggested algorithm is implemented as software and verified by some test cases.

• Tunnel and Underground Space
• /
• v.10 no.3
• /
• pp.486-491
• /
• 2000

Blasting vibrations velocity had been used to design blasting pattern and predict damage-possibility of structures. As vibration levels are currently required to estimate the damage concerning human-body and livestock, so measured vibration velocities must be transformed into vibration levels. In this study, the digital filter program was developed to transform measured data into vibration levels. Simple harmonic vibrations and measured data obtain by Blastmate series (Instantel Inc.) were applied to the digital filter program. As a result, simple harmonic vibrations and measured data were successfully transformed into vibration levels using the developed program. Measured data from any instrument with ASCII output-function will similarly be transformed into level units.

• Proceedings of the Korean Society for Rock Mechanics Conference
• /
• 2000.09a
• /
• pp.241-246
• /
• 2000

Blasting vibrations velocity had been used to design blasting pattern and predict damage-possibility of structures. As vibration levels are currently required to estimate the damage concerning human-body and livestock, so measured vibration velocities must be transformed into vibration levels. In this study, the digital filter program was developed to transform measured data into vibration levels. Simple harmonic vibrations and measured data obtained by Blastmate series (Instantel Inc.) were applied to the digital filter program. As a result, simple harmonic vibrations and measured data were successfully transformed into vibration levels using the developed program. Measured data from any instrument with ASCII output-function will similarly be transformed into level units.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.6
• /
• pp.1070-1079
• /
• 2016

In this paper, the design of recursive radial basis function neural networks based on incremental fuzzy c-means is introduced for processing the big data. Radial basis function neural networks consist of condition, conclusion and inference phase. Gaussian function is generally used as the activation function of the condition phase, but in this study, incremental fuzzy clustering is considered for the activation function of radial basis function neural networks, which could effectively do big data processing. In the conclusion phase, the connection weights of networks are given as the linear function. And then the connection weights are calculated by recursive least square estimation. In the inference phase, a final output is obtained by fuzzy inference method. Machine Learning datasets are employed to demonstrate the superiority of the proposed classifier, and their results are described from the viewpoint of the algorithm complexity and performance index.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2005.11a
• /
• pp.226-229
• /
• 2005

In this study, a step-down piezoelectric transformer was fabricated to utilize as an adapter for charging batteries of mobile electronic appliances. The ceramic part of the transformer is $Pb[(Mn_{1/3}Sb_{2/3})_{0.05}Zr_{0.475}Ti_{0.475}]O_3$ with mechanical quality factor of 1600, electromechanical coupling coefficient 59 %, and piezoelectric constant d33 1300, which can be utilized as a piezoelectric transformer. A simply fabricated disk-typed test pattern of diameter 28 mm and thickness 2 mm was used to characterize resonant frequency, Qm, kp according to the different input/output electrode area. efficiency and power as a function of load resistance was also investigated. The sample APT showed some spurious mode and BPT showed better frequency property. Taking all properties which are admittance, effective electromechanical coupling coefficient and mechanical quality factor most suitable for piezoelectric transformer is BPT which has 12 mm diameter electrode and the condition of 15 Vrms, 30 $\Omega$ made the maximum efficiency of 93.7 % and maximum power is 6W with 50 Vrms.

• Proceedings of the Korean Information Science Society Conference
• /
• 2008.06c
• /
• pp.26-30
• /
• 2008

Currently an automated methodology based on data mining techniques is presented for the prediction of customer load patterns in long duration load profiles. The proposed our approach consists of three stages: (i) data pre-processing: noise or outlier is removed and the continuous attribute-valued features are transformed to discrete values, (ii) cluster analysis: k-means clustering is used to create load pattern classes and the representative load profiles for each class and (iii) classification: we evaluated several supervised learning methods in order to select a suitable prediction method. According to the proposed methodology, power load measured from AMR (automatic meter reading) system, as well as customer indexes, were used as inputs for clustering. The output of clustering was the classification of representative load profiles (or classes). In order to evaluate the result of forecasting load patterns, the several classification methods were applied on a set of high voltage customers of the Korea power system and derived class labels from clustering and other features are used as input to produce classifiers. Lastly, the result of our experiments was presented.