• Advances in aircraft and spacecraft science
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• v.10 no.6
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• pp.545-554
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• 2023

The widespread introduction of unmanned aircrafts has led to the understanding of the need to organize a common information space for manned and unmanned aircrafts, which is reflected in the Russian Unmanned aircraft system Traffic Management (RUTM) project. The present article deals with the issues of spatial information database (DB) organization, which is the core of RUTM and provides storage of various data types (spatial, aeronautical, topographical, meteorological, vector, etc.) required for flight safety management. Based on the analysis of functional capabilities and types of work which it needs to ensure, the architecture of spatial information DB, including the base of source information, base of display settings, base of vector objects, base of tile packages and also a number of special software packages was proposed. The issues of organization of these DB, types and formats of data and ways of their display are considered in detail. Based on the analysis it was concluded that the optimal construction of the spatial DB for RUTM system requires a combination of different model variants and ways of organizing data structures.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1573-1583
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• 2016

It is necessary to check mutual correlations between related variables because housing prices are influenced by a lot of variables of the economy both internally and externally. In this paper, employing the Granger causality test, we have validated interrelated relationship between the variables. In addition, there is cointegration associations in the results of the cointegration test between the variables. Therefore, an analysis using a vector error correction model including an error correction term has been attempted. As a result of the empirical comparative analysis of the forecasting performance with ARIMA and VAR models, it is confirmed that the forecasting performance by vector error correction model is superior to those of the former two models.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.51-56
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• 2005

There are many sources of systematic variations in cDNA microarray experiments which affect the measured gene expression levels like differences in labeling efficiency between the two fluorescent dyes. Print-tip lowess normalization is used in situations where dye biases can depend on spot overall intensity and/or spatial location within the array. However, print-tip lowess normalization performs poorly in situation where error variability for each gene is heterogeneous over intensity ranges. We proposed the new print-tip normalization methods based on support vector machine regression(SVMR) and support vector machine quantile regression(SVMQR). SVMQR was derived by employing the basic principle of support vector machine (SVM) for the estimation of the linear and nonlinear quantile regressions. We applied our proposed methods to previous cDNA micro array data of apolipoprotein-AI-knockout (apoAI-KO) mice, diet-induced obese mice, and genistein-fed obese mice. From our statistical analysis, we found that the proposed methods perform better than the existing print-tip lowess normalization method.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.4
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• pp.408-413
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• 2014

In this paper, we propose a fault diagnosis method based on Park's Vector Approach using the Euler's theorem. If we interpreted it as Euler's theorem, it is possible to easily find the phase angle difference between the healthy condition and the fault condition. And, we analyzed the variation of the phase angle and performed the diagnostic method of the induction motor using feature vectors that were obtained by using a Fourier transform. The analysis of time and speed variation of the motor was performed and, as a result, we could find more soft variations than rough variations. In particular, the analysis of the distortion through each phase shows that two-turn and four-turn shorted motors are linearly separable. In this experiment, we know that the maximum breakdown threshold value for determining steady-state fault detection is 49.0788. Simulation and experimental results show the more detectable than conventional method.

• Journal of Power Electronics
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• v.4 no.2
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• pp.77-86
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• 2004

This paper presents a novel three-phase power module bridge type auxiliary resonant AC link snubber for the three-phase voltage-fed sinwave soft switching PWM inverter operating under specific instantaneous space voltage vector modulation. The operating principle of this resonant snubber is described for current source load model during one switching period, along with its design approach based on the simulation data. The performance evaluations of space vector modulation three-phase sinewave soft switching inverter with a new three-phase active auxiliary resonant AC link snubber are discussed as compared with those of three-phase voltage source-fed sinewave hard switching PWM inverter with a standard space voltage vector modulation strategy. The power loss analysis and conventional efficiency estimation of three-phase soft switching PWM inverter using ICBT modules are carried out including all the conduction power losses based upon the measured v-i characteristics of IGBT and its antiparallel diode as well as their switching losses.

• Journal of Power Electronics
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• v.2 no.2
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• pp.77-87
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• 2002

The purpose of this paper is to improve power conversion efficiency of three-phase soft-switching voltage-source inverter with an auxiliary resonant dc link (ARDCL) snubber circuit. Firstly, the operation principle of ARDCL snubber circuit is described. Secondly, this paper proposes an effictive generation method of zero voltage vector for three-phase voltage-source soft-switching inverter in power losses in which power losses in the ARDCL snubber circuit can be reduced. In particular, zero voltage holding interval in the inverter DC busline can be controlled due to the new generation scheme of zero voltage vector. Thirdly, a simulator for power loss analysis for power loss characteristics based on actual system, is developed. the validity of developed. The validity of developed simulator of proved with experimental results. Finally, power efficency of three-phase inverter is estimated according to high carrier frequency by using the simulatior.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.495-499
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• 2000

The booming noise of a vehicle is usually caused by the vibration of the vehicle's body transmitted from the engine through the mounting system. Thus the engine mounting system must be cautiously designed to reduce the noise. Vector synthesis analysis is performed to predict the booming noise when the characteristic of the engine mounting system is changed., i.e., when magnitudes and phases of vibratory forces after the mounts are altered. To effectively use the method, the concept of 'effectiveness' is introduced to identify the contributions of each vibration sources and transmission paths to interior noise. When the magnitudes and phases of the forces due to the engine vibration are changed, the synthesized interior booming noise level is predicted by the vector synthesis diagram. Thus, the optimum characteristics of the forces are obtained through the simulations of the vector synthesis analysis. It is shown that the vector synthesis method can be used to obtain the optimum design characteristic of the mounting system to control the interior booming noise of a vehicle.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1500-1511
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• 2017

The purpose of this paper is to study a high-performance control scheme for neutral-point-clamping three-level (NPC-3L) inverter fed dual three-phase permanent magnet synchronous motor (PMSM) drives by considering some asymmetric factors such as the non-identical parameters in phase windings. To implement this, the system model is analyzed for dual three-phase PMSM drives with asymmetric factors based on the vector space decomposition (VSD) principle. Based on the equivalent circuits, PI controllers with feedforward compensation are used in the d-q subspace for regulating torque, where the cut-off frequency of the PI controllers are set at the twice the fundamental frequency for compensating both the additional DC component and the second order component caused by asymmetry. Meanwhile, proportional resonant (PR) controllers are proposed in the x-y subspace for suppressing the possible unbalanced currents in the phase windings. A dual three-phase space vector modulation (DT-SVM) is designed for the drive, and the balancing factor is designed based on the numerical fitting surface for balancing the DC link capacitor voltages. Experimental results are given to demonstrate the validity of the theoretical analysis and the proposed control scheme.

• Journal of Korean Medical classics
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• v.32 no.1
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• pp.61-74
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• 2019

Objectives : The purpose of this study is to help select an appropriate word embedding method when analyzing East Asian traditional medicine texts as data. Methods : Based on prescription data that imply traditional methods in traditional East Asian medicine, we have examined 4 count-based word embedding and 2 prediction-based word embedding methods. In order to intuitively compare these word embedding methods, we proposed a "prescription generating game" and compared its results with those from the application of the 6 methods. Results : When the adjacent vectors are extracted, the count-based word embedding method derives the main herbs that are frequently used in conjunction with each other. On the other hand, in the prediction-based word embedding method, the synonyms of the herbs were derived. Conclusions : Counting based word embedding methods seems to be more effective than prediction-based word embedding methods in analyzing the use of domesticated herbs. Among count-based word embedding methods, the TF-vector method tends to exaggerate the frequency effect, and hence the TF-IDF vector or co-word vector may be a more reasonable choice. Also, the t-score vector may be recommended in search for unusual information that could not be found in frequency. On the other hand, prediction-based embedding seems to be effective when deriving the bases of similar meanings in context.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1385-1397
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• 2018

There are many factors that affect the wind speed. In addition, the randomness of wind speed also leads to low prediction accuracy for wind speed. According to this situation, this paper constructs the short-time forecasting model based on the least squares support vector machines (LSSVM) to forecast the wind speed. The basis of the model used in this paper is support vector regression (SVR), which is used to calculate the regression relationships between the historical data and forecasting data of wind speed. In order to improve the forecast precision, historical data is clustered by cluster analysis so that the historical data whose changing trend is similar with the forecasting data can be filtered out. The filtered historical data is used as the training samples for SVR and the parameters would be optimized by particle swarm optimization (PSO). The forecasting model is tested by actual data and the forecast precision is more accurate than the industry standards. The results prove the feasibility and reliability of the model.