• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.69-85
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• 2019

BeiDou navigation satellite system (BDS) is one of the four main types of global navigation satellite systems. The current system has been widely used by the military and by the aerospace, transportation, and marine fields, among others. However, challenges still remain in the BeiDou system, which requires rapid responses for delay-sensitive devices. A differential positioning algorithm called the data center-based differential positioning (DCDP) method is widely used to avoid the influence of errors. In this method, the positioning information of multiple base stations is uploaded to the data center, and the positioning errors are calculated uniformly by the data center based on the minimum variance or a weighted average algorithm. However, the DCDP method has high delay and overload risk. To solve these problems, this paper introduces edge computing to relieve pressure on the data center. Instead of transmitting the positioning information to the data center, a novel method called edge computing-based differential positioning (ECDP) chooses the nearest reference station to perform edge computing and transmits the difference value to the mobile receiver directly. Simulation results and experiments demonstrate that the performance of the ECDP outperforms that of the DCDP method. The delay of the ECDP method is about 500ms less than that of the DCDP method. Moreover, in the range of allowable burst error, the median of the positioning accuracy of the ECDP method is 0.7923m while that of the DCDP method is 0.8028m.

• Journal of the Speleological Society of Korea
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• v.14 no.15
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• pp.42-90
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• 1987

Lee, Moon Won reported by 63 kinds lescribing the petrography and bulk chemical Composition in Petrology of Cheju volcanic island. The total Chemical Composition data was analyzed by the program of FORTRAN77. First, the Conversition equations and the scatter diagram were examined to the analysis, by the least square method. Next, a statistical data requested a mean Value, maximum value, minimum value, the range, the standard deviation, the variance, the Standord Error and the Coefficient of variation. In the standard deviation, a small Composition is MnO and P$_2$O$\sub$5/, a large Composition is SiO$_2$, Mgo and FeO. The Standard error and the variance were the tandency looked like the Standard deviation well. However, the Coefficient Variation differs from the Standard deviation. Where, a large Coefficient of variation are H$_2$O$\^$-/ and H$_2$O$\^$+/, a small Coefficient of variation are Al$_2$O$_3$ and SiO$_2$. The Correlation of Coefficient Can be Calculated numerically from the relation between SiO$_2$, Al$_2$O$_3$ and TiO$_2$ to other Compositions.

• Journal of Navigation and Port Research
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• v.35 no.10
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• pp.785-791
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• 2011

This paper describes the evaluation and selection of MEMS(Micro-Elect Mechanical System) based inertial sensor to fit to implement the Inertial Measurement Unit(IMU) for a small-sized vessel at sea. At first, the error model and the noise model of the inertial sensors are defined with Euler's equations and then, the inertial sensor evaluation is carried out with Allan Variance techniques and Monte Carlo simulation. As evaluation results for the five sensors, ADIS16405, SAR10Z, SAR100Grade100, LIS344ALH and ADXL103, the combination of gyroscope and accelerometer of ADIS16405 is shown minimum error having around 160 m/s standard deviation of velocity error and around 35 km standard deviation of position error after 600 seconds. Thus, we select the ADIS16405 inertial sensor as a MEMS-based inertial sensor to implement IMU and, the error reducing method is also considered with the search for reference papers.

• The Journal of the Acoustical Society of Korea
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• v.23 no.8
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• pp.570-575
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• 2004

In the underwater acoustic systems. we can receive signals and retrieve information about a target by using a beamforming method. The most important thing in the beamforming is finding the way to optimize the mainlobe beamwidth and the sidelobe level to the desired value. One of the prominent results of beamforming method. which has been studied. is Philip's weighting function method(1) . Philip's method adaptively adjusts its weights of array to meet the desired mainlobe beamwidth and sidelobe level. It is very similar to the design method in adaptive filter. However. this method cannot easily bring us to the desired sidelobe level due to complementary relation between mainlobe beamwidth and sidelobe level. In this paper, we propose a new algorithm using partial constrained adaptation. This method makes us circumvent the above problem and meet the specification of design easily. The proposed algorithm presents a Pattern synthesis that designer can easily control the mainlobe beamwidth and the sidelobe level to the desired value while calculation time to converge is decreasing.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.4
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• pp.330-336
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• 2016

In this paper, we studied for modified bartlett method to estimate desired information signal. Constrained length of bartlett method is assigned as one, and estimate desired information signal to compensate for delay time. Modified bartlett method is an optimum direction-of-arrival (DoA) estimation algorithm to apply delay time compensation to update optimum weight. The optimum weight is used linear constrained minimum variance method(LCMV). Through simulation, we are comparative analysis proposed algorithm and general Bartlett and MUSIC method. In desired signal estimation, condition simulation is an array antenna element numbers 6 or 9 and desired information signals number 3. We show the superior performance of the proposed algorithm relative to the existing method in estimation of desired information signal.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3D
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• pp.347-356
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• 2009

This paper is described clustering analysis of traffic characteristics-based highway classification in order to deviate from methodologies of existing highway functional classification. This research focuses on comparing the clustering techniques performance based on the total within-group errors and deriving the optimal number of cluster. This research analyzed statistical clustering method (Hierarchical Ward's minimum-variance method, Nonhierarchical K-means method) and Kohonen self-organizing maps clustering method for highway characteristic classification. The outcomes of cluster techniques compared for the number of samples and traffic characteristics from subsets derived by the optimal number of cluster. As a comprehensive result, the k-means method is superior result to other methods less than 12. For a cluster of more than 20, Kohonen self-organizing maps is the best result in the cluster method. The main contribution of this research is expected to use important the basic road attribution information that produced the highway characteristic classification.

• Journal of the Korean Geotechnical Society
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• v.27 no.8
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• pp.51-61
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• 2011

Spatial estimation of the thickness and depth of the geological profile has been regarded as an important procedure for the design of soft ground. A minimum variance criterion, which has often been used in traditional kriging techniques, does not always guarantee the optima1 estimates for the decision-making process in geotechnical engineering. In this study, a geostatistica; framework is used to determine the optimal thickness of the consolidation layer and the optimal area that needs the adoption of prefabricated vertical drains via indicator kriging and loss function. From the exemplary problem, different optimal estimates can be obtained depending on the loss function chosen. The design procedure and method considering the minimum expected loss presented in this paper can be used in the decision-making process for geotechnical engineering design.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.6
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• pp.7-14
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• 2017

This study manufactured a minimum quantity lubrication (MQL) supply system and identified the optimal MQL machining cutting conditions for plastic mold steel (SCM440). A series of experiments were consisted of twice. Optimal cutting conditions were derived using the Taguchi method, and cutting force variance; surface roughness; tool wear; and cutting temperature in dry, wet, and MQL machining were measured experimentally for these optimal conditions. The measured results decreased from dry to wet and MQL machining, being particularly large for dry machining due to increased cutting time. Measured MQL machining metrics were similar to those for wet machining, particularly for surface roughness, which is an index of machining quality.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.5
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• pp.85-95
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• 2021

Structure design sensitivity was evaluated using the orthogonal array experimental method for passive-type deck support frame (DSF) developed for float-over installation of the offshore plant. Moreover, approximation characteristics were also reviewed based on various meta-models. The minimum weight design of the DSF is significantly important for securing both maneuvering performance and buoyancy of a ship equipped with the DSF and guaranteeing structural design safety. The performance strength of the passive type DSF was evaluated through structure analysis based on the finite element method. The thickness of main structure members was applied to design factors, and output responses were considered structure weight and strength performances. Quantitative effects on the output responses for each design factor were evaluated using the orthogonal array experimental method and analysis of variance. The optimum design case was also identified from the orthogonal array experiment results. Various meta-models, such as Chebyshev orthogonal polynomial, Kriging, response surface method, and radial basis function-based neural network, were generated from the orthogonal array experiment results. The results of the orthogonal array experiment were validated using the meta-modeling results. It was found that the radial basis function-based neural network among the meta-models could approximate the design space of the passive type DSF with the highest accuracy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.89-93
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• 2013

This paper is estimating a target direction of arrival with incident to receiver in spatial. This paper presented covariance using constraint matrix to correlation interference signal cancellation in multi input multi output array antennas system. we proposed a target direction of arrival estimation algorithm using cost function and minimum variance method. Through simulation, we were analysis a performance to compare general SPT-LCMV algorithm and proposal algorithm. We showed that proposal algorithm improve more target estimation than general SPT-LCMV algorithm in direction of arrival.