• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2005.05a
• /
• pp.292-297
• /
• 2005

This paper proposes a simple MPPT control scheme of a Current-Control-Loop Error system Based that can be obtains a lot of advantage to compare with another digital control method, P&O and IncCond algorithm, that is applied mostly a PV system. An existent method is needed an expensive processor such as DSP that calculated to change the measure power of a using current and voltage sensor at the once. Therefore, it is applied a small home power generation system that required many expenses. But, a proposed method is easy to solve the cost reduction and power unbalance problems that it is used by control scheme to limit error of a current control of common sensor. This proposed algorithm had verified through a simulation and an experiment on battery charger using PIC that is the microprocessor of a low price.

• Journal of KIISE
• /
• v.43 no.6
• /
• pp.636-644
• /
• 2016

Annotated Corpus is important to understand natural language using machine learning method. In this paper, we propose a new method to automate error reduction of annotated corpora. We use the Ripple-Down Rules(RDR) for reducing errors and Kernel to extend RDR for NLP. We applied our system to the Korean Wikipedia and blog corpus errors to find the annotated corpora error type. Experimental results with various views from the Korean Wikipedia and blog are reported to evaluate the effectiveness and efficiency of our proposed approach. The proposed approach can be used to reduce errors of large corpora.

• Structural Engineering and Mechanics
• /
• v.43 no.3
• /
• pp.371-394
• /
• 2012

Accurate finite element (FE) models are needed in many applications of Civil Engineering such as health monitoring, damage detection, structural control, structural evaluation and assessment. Model accuracy depends on both the model structure (the form of the equations) and the model parameters (the coefficients of the equations), and can be generally improved through that process of experimental reconciliation known as model updating. However, modelling errors, including (i) errors in the model structure and (ii) errors in parameters excluded from adjustment, may bias the solution, leading to an updated model which replicates measurements but lacks physical meaning. In this paper, an application of ambient-vibration-based model updating to a large-scale benchmark prototype of a building structure is reported in which both types of error are met. The error in the model structure, originating from unmodelled secondary structural elements unexpectedly working as resonant appendages, is faced through a reduction of the experimental modal model. The error in the model parameters, due to the inevitable constraints imposed on parameters to avoid ill-conditioning and under-determinacy, is faced through a multi-model parameterization approach consisting in the generation and solution of a multitude of models, each characterized by a different set of updating parameters. Results show that modelling errors may significantly impair updating even in the case of seemingly simple systems and that multi-model reasoning, supported by physical insight, may effectively improve the accuracy and robustness of calibration.

• Journal of Satellite, Information and Communications
• /
• v.10 no.1
• /
• pp.22-28
• /
• 2015

In this paper, we propose a new computationally efficient joint iterative multi-input multi-output (MIMO) detection scheme using a soft interference cancellation and minimum mean squared-error (SIC-MMSE) method. The critical computational burden of the SIC-MMSE scheme lies in the multiple inverse operations of the complex matrices. We find a new way which requires only a single matrix inversion by utilizing the Taylor series expansion of the matrix, and thus the computational complexity can be reduced. The computational complexity reduction increases as the number of antennas is increased. The simulation results show that our method produces almost the same performances as the conventional SIC-MMSE with reduced computational complexity.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.47 no.5
• /
• pp.41-47
• /
• 2010

This paper has proposed parallel BCH, one of error correction coding methods which has been used to NAND flash memory for SSD(solid state disk). To alter error correction capability, the proposed design improved reliability on data block has higher error rate as used frequency increasingly. Decoding parallel process bit width is as two times as encoding parallel process bit width, that could reduce decoding processing time, accordingly resulting in one half reduction over conventional ECC.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.41 no.5
• /
• pp.335-341
• /
• 2013

The variation of systematic bias errors in the wind tunnel testing has been studied. A Design of Experiments(DOE) approach to an experimental study of fuselage drag and stability characteristics of a helicopter configuration was applied. When forces and moments measured in one time block differ significantly from measurements made in another time block under assumption that sample observations can be expected to yield same results within permissible measuring errors. The practical implication of this paper is that the systematic error can not be assumed not to exist. The those error reduction could be achieved through the process of randomization, blocking, and replication of the data points.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.2
• /
• pp.339-346
• /
• 2017

This paper proposes a sensorless control method to improve the performance of an internal permanent magnet synchronous motor (IPMSM) control by using a full-order flux observer in a wide speed range. The conventional sensorless control method uses a constant gain for high performance at low-speed region. However, this method has drawbacks such as an increased angle error and current ripple in the high-speed region due to the fixed gain value. In order to overcome this problem, the gain of the full-order flux observer is changed by considering the angle error in the whole speed range. The proposed method minimizes the angle error for each region of the speed range by applying a relevant gain value, which improves the current ripple reduction and motor noise cancellation. The validity of proposed sensorless control method is verified by a simulation and an experiment.

• Journal of Information Technology Services
• /
• v.11 no.1
• /
• pp.211-221
• /
• 2012

Many metric-based classification models have been proposed to predict fault-proneness of software module. This paper presents two prediction models using Bayesian classifier which is one of the most popular modern classification algorithms. Bayesian model based on Bayesian probability theory can be a promising technique for software quality prediction. This is due to the ability to represent uncertainty using probabilities and the ability to partly incorporate expert's knowledge into training data. The two models, Na$\ddot{i}$veBayes(NB) and Bayesian Belief Network(BBN), are constructed and dimensionality reduction of training data and test data are performed before model evaluation. Prediction accuracy of the model is evaluated using two prediction error measures, Type I error and Type II error, and compared with well-known prediction models, backpropagation neural network model and support vector machine model. The results show that the prediction performance of BBN model is slightly better than that of NB. For the data set with ambiguity, although the BBN model's prediction accuracy is not as good as the compared models, it achieves better performance than the compared models for the data set without ambiguity.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.5
• /
• pp.912-920
• /
• 2008

OFDM (Orthogonal Frequency Division Multiplexing) system is robust to frequency selective fading and narrowband interference in high-speed data communications. However, an OFDM signal consists of a number of independently modulated subcarriers, which can give a large PAPR (Peak-to-Average Power Ratio) when added up coherently. In this paper, we apply clipping and filtering to solve the PAPR problem and compensate the inband compensation using calculated EVM (Error Vector Magnitude). The proposed method can reduce the PAPR and inband distortion. From the results, we analyze the PAPR reducing efficiency and EVM, BER performance of proposed algorithm in the wireless communication system.

• Asia-Pacific Journal of Business
• /
• v.10 no.2
• /
• pp.13-26
• /
• 2019

This paper aims to empirically examine the short-run and long-run aggregate demand for the US imports using quarterly economic data for the period 2000-2018 including aggregate imports, final expenditure components, gross fixed capital formation and relative price of imports. According to the results of both multivariate co-integration analysis and error correction model, the above variables are all cointegrated and significant differences are found to exist among the long-run partial elasticities of imports as regards different macro components of final expenditure. Partial elasticities with respect to government expenditure, gross fixed capital formation, exports and relative price of import are found to be positive while imports seems to respond negatively to changes in private consumption, implying that an increase in private consumption could result in a significant reduction in demand for imports in the long run. With regard to the relative import prices, the results appear to indicate a relatively insignificant influence on the aggregate imports in the US in the long run. However, an error correction model designed for predicting the short-term variability shows that only exports have an impact on the imports in the short run.