• Proceedings of the SCSK Conference
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• 2003.09a
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• pp.225-231
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• 2003

To search and development a new material with superior melanogenesis inhibitory activity, the bioactivities (obs. pl$_{50}$) of alkyl-3,4-dihydroxybenzoyl esters and N-alkyl-3,4-dihydroxybenz-oyl amides as substrate molecules were measured in mouse melanoma cells. And also, we have studied that 3-D QSARs (3 dimensional Quantitative Structure-Activity Relationships) between molecular interaction field of substrates and the bioactivities were analyzed using CoMFA (Comparative Molecular Field Analyses) method. When cross-validation value (q$^2$) is 0.68 at 3 components, the Pearson correlation coefficient ($r^2$) is 0.900. From the basis on the findings, the model was appeared by the contour map such as steric field and electrostatic field relationships between quantitative structure and the bioactivity of the various substrate derivatives. Measured bioactivities (obs. pl$_{50}$) of unknown compounds are very similar to predicted activity (pred. pl$_{50}$) according to the CoMFA model. As the results of prediction, we could conclude that the bioactivities were increased by creation of R$_1$ substitution of 5,5-dime-thylhexoxy, 6,6-dimethylheptyl, 1-amino-6,6-dimethylheptyl group etc and R$_2$ substitution of hydroxy, methyl, methoxy group etc.p etc.

• Proceedings of the KSRS Conference
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• v.1
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• pp.166-169
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• 2006

Our country's coast is vulnerable area to natural disaster which the repetitive damages occur every year including a loss of lives, the damage of facilities and erosion mostly except for the east coast because of a typhoon, tidal waves, sea water overflowing by topographic structure of low-lying gentle slope and shallow sea. However, as for prevention of natural disaster occurring every year, the situation is that it's centered on the restorationcentered measures and the general disaster prevention research to minimize damages at the time of disaster occurrence is insufficient. This study intendedlop t to devehe techniques possible for real time sampling of damage prediction areas on Web in order to support decision making for damage prevention and establishment of disaster prevention policy. For this, the thematic map was produced related to disaster based on high-resolution satellite picture, and the environmental DB similar to real world was constructed through topographic construction of three-dimension integrating the parts of land and the sea. In addition, the system was developed possible for the expression of damageable regions by real time grasp of dangerous regions at the time of disaster occurrence through over flowing simulation of three-dimension, and it's intended to prepare a basis to minimize damages to disaster situations through it.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2003.05a
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• pp.105-109
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• 2003

A new scaling method for the prediction of gas turbine components characteristics using experimental data of gas turbine test unit has been proposed. In order to minimize the analyzed performance error in the this study, firstly component maps were constructed by real experimental performance data at some operating conditions and a polynomial obtained from scaling factors at given conditions, and then the simulated performance using the identified maps was compared with the performance result using the currently used traditional scaling method. In comparison, the performance analysis result by the currently used traditional scaling method was met well agreed with the real engine performance at most off-design points except for the design point. However the performance analysis result using the newly proposed scaling method had good agreement with the experimental results within maximum 5％ error.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.642-649
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• 2012

This paper deals with a copper die casting induction motor which has several advantages of motor performance. The developed motor is used as spindle motor in machining center. The dynamic characteristic analysis of rotor is dealt with for precision machining. The critical speed of rotor considering rotation and gyroscopic effect should be above operating speed, 18,000 rpm, and have a 201 % sufficient separation margin. Also, the 3-D unbalance vibration response analysis is performed and enabled the prediction of the expected vibration amplitude by unbalance in high speed. The unbalance vibration responses of each position on the rotor are satisfied with allowable vibration displacement of API 611 standard according to balancing G grade(G 0.4, G 2.5, G 6.3). Copper die casting high speed induction motor is successfully developed and verified by experiment.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.83-92
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• 2020

The purpose of this work was to apply geographical information system (GIS) for geostatistical analyzing by selecting a semi-variogram model to quantify the spatial correlation of the population distribution with residential neighborhoods in the both sides of Mosul city. Two hundred and sixty-eight sample sites in 240 ㎢ are adopted. After determining the population distribution with respect to neighborhoods, data were inserted to ArcGIS10.3 software. Afterward, the datasets was subjected to the semi-variogram model using ordinary kriging interpolation. The results obtained from interpolation method showed that among the various models, Spherical model gives best fit of the data by cross-validation. The kriging prediction map obtained by this study, shows a particular spatial dependence of the population distribution with the neighborhoods. The results obtained from interpolation method also indicates an unbalanced population distribution, as there is no balance between the size of the population neighborhoods and their share of the size of the population, where the results showed that the right side is more densely populated because of the small area of residential homes which occupied by more than one family, as well as the right side is concentrated in economic and social activities.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.387-392
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• 1998

To establish a monthly data collection planning for the Ocean Scanning Multispectral Imager (OSMI), we have examined the global patterns of three impacting factors: pigment concentration, cloud cover, and sun glint. Other than satellite mission constraints (e.g., duty cycle), these three factors are considered critical for the OSMI data collection. The Nimbus-7 Coastal Zone Color Scanner (CZCS) monthly mean products and the International Satellite Cloud Climatology Project (ISCCP) monthly mean products (C2) were used for the analysis of pigment concentration and cloud cover distributions, respectively. And the monthly simulated patterns of sun glint were produced by performing the OSMI orbit prediction and the calculation of sun glint radiances at the top-of-atmosphere (TOA). Using monthly statistics (mean and/or standard deviation) of each factor in the above for a given 10$^{\circ}$ latitude by 10$^{\circ}$ longitude grid, we generated the priority map for each month. The priority maps of three factors for each month were subsequently superimposed to visualize the impact of three factors in all. The initial results illustrated that a large part of oceans in the summer hemisphere was classified into the low priority regions because of seasonal changes of clouds and sun illumination. Sensitivity tests were performed to see how cloud cover and sun glint affect the priority determined by pigment concentration distributions, and consequently to minimize their seasonal effects upon the data collection planning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3966-3991
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• 2018

Due to the lack of visualization services and organic combinations between public and private buildings data, the usability of the basic map has remained low. To address this issue, this paper reports on a solution that organically combines public and private data while providing visualization services to general users. For this purpose, factors that can affect building prices first were examined in order to define the related data attributes. To extract the relevant data attributes, this paper presents a method of acquiring public information data and real estate-related information, as provided by private real estate portal sites. The paper also proposes a pretreatment process required for intelligent machine learning. This report goes on to suggest an intelligent machine learning algorithm that predicts buildings' value pricing and future value by using big data regarding buildings' spatial information, as acquired from a database containing building value attributes. The algorithm's availability was tested by establishing a prototype targeting pilot areas, including Suwon, Anyang, and Gunpo in South Korea. Finally, a prototype visualization solution was developed in order to allow general users to effectively use buildings' value ranking and value pricing, as predicted by intelligent machine learning.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.101.2-101.2
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• 2011

We have developed solar and space weather monitoring system for space weather users since 2007 as a project named 'Construction of Korea Space Weather Prediction Center'. In this presentation we will introduce space weather monitoring system for Geostationary Satellites and Polar Routes. These were developed for satisfying demands of space weather user groups. 'Space Weather Monitoring System for Geostationary Satellites' displays integrated space weather information on geostationary orbit such as magnetopause location, nowcast and forecast of space weather, cosmic ray count rate, number of meteors and x-ray solar flux. This system is developed for space weather customers who are managing satellite systems or using satellite information. In addition, this system provides space weather warning by SMS in which short message is delivered to users' cell phones when space weather parameters reach a critical value. 'Space Weather Monitoring System for Polar Routes' was developed for the commercial airline companies operating polar routes. This provides D-region and polar cap absorption map, aurora and radiation particle distribution, nowcast and forecast of space weather, proton flux, Kp index and so on.

• Journal of Integrative Natural Science
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• v.4 no.2
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• pp.91-98
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• 2011

Quantitative structure-activity relationships (QSAR) have been applied for two decades in the development of relationships between physicochemical properties of chemical substances and their biological activities to obtain a reliable statistical model for prediction of the activities of new chemical entities. The fundamental principle underlying the QSAR is that the structural difference is responsible for the variations in biological activities of the compounds. In this work, we developed 3D-QSAR model for a series of 5-Lipoxygenase inhibitors, utilizing comparative molecular field analysis (CoMFA) and Topomer CoMFA methodologies. Our developed models addressed superiority of Topomer CoMFA over CoMFA. The CoMFA model was obtained with $q^2$=0.593, $r^2$=0.939, $Q^2$=0.334 with 6 optimum number of components (ONC). Higher statistical results were obtained with the Topomer CoMFA model ($q^2$=0.819, $r^2$=0.947, ONC=5). Further robustness of developed models was checked with the ANOVA test and it shows F=113 for CoMFA and F=162.4 for Topomer CoMFA model. Contour map analysis indicated that the more requirement of electrostatic parameter for improved potency.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.995-1005
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• 2011

An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.