• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.833-842
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• 2017

In this study, the design methodology of radial basis function neural networks based on incremental K-means clustering is introduced for learning and processing the big data. If there is a lot of dataset to be trained, general clustering may not learn dataset due to the lack of memory capacity. However, the on-line processing of big data could be effectively realized through the parameters operation of recursive least square estimation as well as the sequential operation of incremental clustering algorithm. Radial basis function neural networks consist of condition part, conclusion part and aggregation part. In the condition part, incremental K-means clustering algorithms is used tweights of the conclusion part are given as linear function and parameters are calculated using recursive least squareo get the center points of data and find the fitness using gaussian function as the activation function. Connection s estimation. In the aggregation part, a final output is obtained by center of gravity method. Using machine learning data, performance index are shown and compared with other models. Also, the performance of the incremental K-means clustering based-RBFNNs is carried out by using PSO. This study demonstrates that the proposed model shows the superiority of algorithmic design from the viewpoint of on-line processing for big data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.510-516
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• 2019

In this paper, a snowboard simulator that measures the user's motion and makes the user feel physical changes and enjoy actual snowboarding was developed. The speed and direction of the snowboard are determined by the user's center of gravity. The developed simulator is equipped with four springs on the snowboard plate, so that the slope can change according to the change in the user's weight center and be felt directly. The slope due to the change in the center of gravity of the user is measured using a three-axis acceleration sensor. The friction of the slope generated by the rotation of the snowboard is made possible by the user using the BLDC motor, and the rotation of the snowboard is measured using the hole sensor. For rapid data processing of the simulator, two MCUs are used to transfer the measured data to the PC using the acceleration sensor and motor separately. The developed simulator can experience slopes and friction of the slope directly, and wear measured data and HMD to enjoy more realistic snowboarding.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.11a
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• pp.64-64
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• 2009

As the advanced packaging technology developing, Copper electro-plating processing has be wildly utilized in the semiconductor interconnect technique. Chemical solution monitoring methods, including PH and gravity measurement exist in industry, but economical and practical real-time monitoring has not been achieved yet. Red-green-blue (RGB) color sensor can successfully monitor the condition of $CuSO_4$ solution during electric copper plating process. Comparing the intensity variations of the RGB data and optical spectroscopy data, strong correlation between two in-situ sensors have shown.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.2
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• pp.49-56
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• 2003

As semi-solid forging (SSF) is compared with conventional casting such as gravity die-casting and squeeze casting, the product without inner defects can be obtained from semi-solid forming and globular microstructure as well. Generally, SSF consists of reheating, forging, and ejecting processes. In the reheating process, the materials are heated up to the temperature between the solidus and liquidus line at which the materials exists in the form of liquid-solid mixture. The process variables such as reheating time, reheating temperature, reheating holding time, and induction heating power has large effect on the quality of the reheated billets. It is difficult to consider all the variables at the same time for predicting the quality. In this paper, Taguchi method, regression analysis and neural network were applied to analyze the relationship between processing conditions and solid fraction. A356 alloy was used for the present study, and the learning data were extracted from the reheating experiments. Results by neural network were in good agreement with those by experiment. Polynominal regression analysis was formulated using the test data from neural network. Optimum processing condition was calculated to minimize the grain size and solid fraction standard deviation or to maximize the specimen temperature average. Discussion is given about reheating process of row material and results are presented with regard to accurate process variables fur proper solid fraction, specimen temperature and grain size.

• Current Industrial and Technological Trends in Aerospace
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• v.6 no.2
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• pp.80-89
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• 2008

Photogrammetry is a non-direct 3-dimensional coordinate measurement technique using 2-dimensional photographic images. For reconstruction 3-dimensional data from the 2-dimensional photos, photogrammetry uses the fundamental principle of triangulation. Digital photogrammetry solve for the camera location and coordinates simultaneously through the mapping, scaling and bundle processing in software processing. In this paper, several applications for photogrammetry measurement are introduced, such as 'photogrammetric measurement of the gravity deformation of a cassegrain type antenna', 'analysis of photogrammetry data from ISIM mockup', 'underwater photogrammetric verification of nuclear fuel assemblies', 'spacecraft optical bench measurement' and 'spacecraft ground support equipment measurement'.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.326-328
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• 2000

The paper proposes the scheme of skew detection for Thai printed document images by using linear regression algorithm. It intends to use with the Thai character recognition systems to reduce the skew detection time. This scheme begins by finding the center of gravity of a document image. This point is used as the starting point for gathering data in the scheme. The data is obtained by scanning incrementally one pixel in vertically with the width of 20-pixels. After the scanning process, if data Is different from it's neighbor more than ${\pm}$ 15 pixels, it will be considered as noise or data in other lines and will be deleted. The last step is the operation by using linear regression algorithm on these selected data and the skew angle will be obtained. The proposed method has been tested with 45 document images with different fonts, sizes and skew angles. The experiment results show that the proposed method can detect the skew angle with the error of less then one degree. The average processing time is about 19 times faster than that of the Hough Transform method.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.961-968
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• 1999

In this paper we handle a system that transform sensor data to sensor information. Sensor informations from redundant accelerometers are manipulated to represent the configuration of objects carrying sensors. Basic sensor unit of the proposed systme is composed of 3 accelerometers that are aligned along x-y-z coordination axes of motion. To refine the sensor information, at first the sensor data are fused by geometrical optimization to reduce the variance of sensor information. To overcome the error caused from inexact alignment of each sensor to the coordination system, we propose a calibration technique that identifies the transformation between the coordinate axes and real sensor axes. The calibration technique make the sensor information approach real value. Also, we propose a technique that decomposes the accelerometer data into motion acceleration component and gravity acceleration component so that we can get more exact configuration of objects than in the case of raw sensor data. A set of experimental results are given to show the usefulness of the proposed method as well as the experiments in which the proposed techniques are applied to human body motion capture.

• Economic and Environmental Geology
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• v.18 no.4
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• pp.309-320
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• 1985

The crustal structure of the southern part of the Korean peninsula has been investigated based on the results of processing and anlaysis of gravity data. The processing techniques involve i) seperation of regional and residual anomalies by polynomial fittings, ii) power spectral analyses to determine the mean depth to the crustal base, iii) a filtering operation called "high-cut filtering and resampling," and iv) downward continuation to determine the undulation of the crustal base. The Bouguer anomalies show a lineation in the NE-SW direction which is the same as that of most mountains and tectonic lines of this area. The mean crustal depth is found to be 34km. The depth of the crustal base is varying in the estimated range of 26km to 36km with a thinner crust below the east coast than that of the west coast. The relief of the crustal base is appeared to be correlated with the regional surface topography. The linear regression relations computed between elevations and gravity anomalies indicate that the crust of this area seems to be not in perfect isostatic equilibrium but a little undercompensated state.

• Journal of Astronomy and Space Sciences
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• v.28 no.1
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• pp.55-62
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• 2011

The precise orbit determination (POD) of low earth orbiter (LEO) has complied with its required positioning accuracy by the double-differencing of observations between International GNSS Service (IGS) and LEO to eliminate the common clock error of the global positioning system (GPS) satellites and receiver. Using this method, we also have achieved the 1 m positioning accuracy of Korea Multi-Purpose Satellite (KOMPSAT)-2. However double-differencing POD has huge load of processing the global network of lots of ground stations because LEO turns around the Earth with rapid velocity. And both the centimeter accuracy and the near real time (NRT) processing have been needed in the LEO POD applications--atmospheric sounding or urgent image processing--as well as the surveying. An alternative to differential GPS for high accuracy NRT POD is precise point positioning (PPP) to use measurements from one satellite receiver only, to replace the broadcast navigation message with precise post processed values from IGS, and to have phase measurements of dual frequency GPS receiver. PPP can obtain positioning accuracy comparable to that of differential positioning. KOMPSAT-5 has a precise dual frequency GPS flight receiver (integrated GPS and occultation receiver, IGOR) to satisfy the accuracy requirements of 20 cm positioning accuracy for highly precise synthetic aperture radar image processing and to collect GPS radio occultation measurements for atmospheric sounding. In this paper we obtained about 3-5 cm positioning accuracies using the real GPS data of the Gravity Recover and Climate Experiment (GRACE) satellites loaded the Blackjack receiver, a predecessor of IGOR. And it is important to reduce the latency of orbit determination processing in the NRT POD. This latency is determined as the volume of GPS measurements. Thus changing the sampling intervals, we show their latency to able to reduce without the precision degradation as the assessment of their precision.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.379-388
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• 2019

Recently, a technique for acquiring spatial information data using UAV (Unmanned Aerial Vehicle) has been greatly developed. It is a very crucial issue of the GIS (Geographic Information System) mapping system that passes way point in the unmanned airframe and finally measures the accurate image and stable localization to the desired destination. Though positioning using DGPS (Differential Global Navigation System) or RTK-GPS (Real Time Kinematic-GPS) guarantee highly accurate, they are more expensive than the construction of a single positioning system using a single GPS. In the case of a low-priced single GPS system, the stability of the positioning data deteriorates. Therefore, it is necessary to supplement the uncertainty of the absolute position data of the UAV and to improve the accuracy of the current position data economically in the operating state of the UAV. The aim of this study was to present an algorithm enhancing the stability of position data in a single GPS mode of UAV with multiple GPS. First, the arrangement of multiple GPS receivers through the center of gravity of the UAV were examined. Next, MD (Mahalanobis Distance) is applied to detect instantaneous errors of GPS data in advance and eliminate outliers to increase the accuracy of previously collected multiple GPS data. Processing procedure for multiple GPS reception data by applying the center of the triangular method were presented to improve the position accuracy. Second, UAV navigation systems integrated multiple GPS through configuration of the UAV specifications were implemented. Using the unmanned airframe equipped with multiple GPS receivers, GPS data is measured with the TCM (Triangular Center Method). In addition, UAV equipped with multiple GPS were operated in study area and locational accuracy of multiple GPS of UAV with VRS (Virtual Reference Station) GNSS surveying were compared. The result showed that the error factors are compensated, and the error range are reduced, resulting in the reliability of the corrected value. In conclusion, the result in this paper is expected to realize high-precision position estimation at low cost in UAV using multiple low-cost GPS receivers.