• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1230-1232
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• 2000

To reduce harmonics in the AC line and achieve a unit power factor, A 4 paralled single phase PWM AC/DC converter has been proposed. In this paper, the coupling components are derived analytically from PWM converter input transformer model and control scheme to solve this problem is proposed. Unit power factor was obtained and the AC-side current harmonics were reduced. Simulation results show the usefulness of the proposed method and applicability to PWM converter in auxiliary block of high speed train.

• ETRI Journal
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• v.42 no.5
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• pp.790-798
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• 2020

Herein, a low-ripple coarse-fine digital low-dropout regulator (D-LDO) without ringing in the transient state is proposed. Conventional D-LDO suffers from a ringing problem when settling the output voltage at a large load transition, which increases the settling time. The proposed D-LDO removes the ringing and reduces the settling time using an auxiliary power stage which adjusts its output current to a load current in the transient state. It also achieves a low output ripple voltage using a comparator with a complete comparison signal. The proposed D-LDO was fabricated using a 65-nm CMOS process with an area of 0.0056 μ㎡. The undershoot and overshoot were 47 mV and 23 mV, respectively, when the load current was changed from 10 mA to 100 mA within an edge time of 20 ns. The settling time decreased from 2.1 ㎲ to 130 ns and the ripple voltage was 3 mV with a quiescent current of 75 ㎂.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.98-103
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• 2021

Recently, as the need for food resources has increased both domestically and internationally, support for the agricultural sector for stable food supply and demand is expanding in Korea. However, according to recent media articles, the biggest problem in rural communities is the unstable profit structure. In addition, in order to confirm the profit structure, profit forecast data must be clearly prepared, but there is a lack of auxiliary data for farmers or future returnees to predict farm income. Therefore, in this paper we analyzed data over the past 15 years through time series analysis and proposes an artificial intelligence farm income prediction algorithm that can predict farm household income in the future. If the proposed algorithm is used, it is expected that it can be used as auxiliary data to predict farm profits.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.342-343
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• 2019

This paper explores the power distribution problem of parallel-connected inverter system which supplies auxiliary power for railway facilities. We propose a droop control method which facilities power distribution and restrain of voltage drop by tracking the average power control command by adjusting the virtual impedance. The performance of proposed droop method is verified by the PSIM simulation.

• Journal of the Korean Mathematical Society
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• v.60 no.2
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• pp.273-302
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• 2023

In this paper, a fully discrete numerical scheme for the viscoelastic Oldroyd flow is considered with an introduced auxiliary variable. Our scheme is based on the finite element approximation for the spatial discretization and the backward Euler scheme for the time discretization. The integral term is discretized by the right trapezoidal rule. Firstly, we present the corresponding equivalent form of the considered model, and show the relationship between the origin problem and its equivalent system in finite element discretization. Secondly, unconditional stability and optimal error estimates of fully discrete numerical solutions in various norms are established. Finally, some numerical results are provided to confirm the established theoretical analysis and show the performances of the considered numerical scheme.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.387-402
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• 2009

In this paper we have considered the problem of estimating the population mean $\bar{Y}$ of the study variable y using auxiliary information in presence of non-response. Classes of estimators for $\bar{Y}$ in the presence of non-response on the study variable y only and complete response on the auxiliary variable x is available, have been proposed in different situations viz., (i) population mean $\bar{X}$ is known, (ii) when population mean $\bar{X}$ and variance $S^2_x$ are known; (iii) when population mean $\bar{X}$ is not known: and (iv) when both population mean $\bar{X}$ and variance $S^2_x$ are not known: single and two-phase (or double) sampling. It has been shown that various estimators including usual unbiased estimator and the estimators reported by Rao (1986), Khare and Srivastava (1993, 1995) and Tabasum and Khan (2006) are members of the proposed classes of estimators. The optimum values of the first phase sample size n', second phase sample size n and the sub sampling fraction 1/k have been obtained for the fixed cost and the fixed precision. To illustrate foregoing, we have carried out an empirical investigation to reflect the relative performance of all the potentially competing estimators including the one due to Hansen and Hurwitz (1946) estimator, Rao (1986) estimator, Khare and Srivastava (1993, 1995) and Tabasum and Khan (2006) estimator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3729-3749
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• 2021

At present, deep convolution network-based salient object detection (SOD) has achieved impressive performance. However, it is still a challenging problem to make full use of the multi-scale information of the extracted features and which appropriate feature fusion method is adopted to process feature mapping. In this paper, we propose a new adjacency auxiliary network (AANet) based on multi-scale feature fusion for SOD. Firstly, we design the parallel connection feature enhancement module (PFEM) for each layer of feature extraction, which improves the feature density by connecting different dilated convolution branches in parallel, and add channel attention flow to fully extract the context information of features. Then the adjacent layer features with close degree of abstraction but different characteristic properties are fused through the adjacent auxiliary module (AAM) to eliminate the ambiguity and noise of the features. Besides, in order to refine the features effectively to get more accurate object boundaries, we design adjacency decoder (AAM_D) based on adjacency auxiliary module (AAM), which concatenates the features of adjacent layers, extracts their spatial attention, and then combines them with the output of AAM. The outputs of AAM_D features with semantic information and spatial detail obtained from each feature are used as salient prediction maps for multi-level feature joint supervising. Experiment results on six benchmark SOD datasets demonstrate that the proposed method outperforms similar previous methods.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.248-251
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• 1999

Recently, according to developing industry and life style, power consumption have been increased year after year. Currently these much power demand from power consumer is weakening the allowable power reverse margin in summer. As on of the remedies about this problem, the small scale grid-connected photovoltaic system is considered for auxiliary power source. Generally, grid-connected inverter have a isolation transformer for electrical isolation from utility. This paper propose transformerless system topology an inquiry the validity using simulation.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1046-1048
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• 1999

This Paper compares two mathematical decomposition coordination methods to implementing the distributed optimal Power flow(OPF) using the regional decomposition: the Auxiliary Problem Principle(APP) and the Alternating Direction Method(ADM), a variant of the conventional Augmented Lagrangian approach. A case study was performed with IEEE 50-bus system.

• Journal of the Korean Statistical Society
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• v.34 no.1
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• pp.73-83
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• 2005

Thompson's (1990) adaptive cluster sampling is a promising sampling technique to ensure effective representation of rare or localized population units in the sample. We consider the problem of simultaneous estimation of the numbers of earners through a number of rural unorganized industries of which some are concentrated in specific geographic locations and demonstrate how the performance of a conventional Rao-Hartley-Cochran (RHC, 1962) estimator can be improved upon by using auxiliary information in the form of generalized regression (greg) estimators and then how further improvements are also possible to achieve by adopting adaptive cluster sampling.