• Bulletin of the Korean Mathematical Society
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• v.51 no.5
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• pp.1357-1368
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• 2014

This paper is concerned with a reaction-diffusion single species model with harvesting on n-dimensional isotropically growing domain. The model on growing domain is derived and the corresponding comparison principle is proved. The asymptotic behavior of the solution to the problem is obtained by using the method of upper and lower solutions. The results show that the growth of domain takes a positive effect on the asymptotic stability of positive steady state solution while it takes a negative effect on the asymptotic stability of the trivial solution, but the effect of the harvesting rate is opposite. The analytical findings are validated with the numerical simulations.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.4
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• pp.126-130
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• 2007

This paper presents a method to design a repetitive controller that is specified in the specified trajectory for the repetitive works. With the single-model design approach, the controller is derived by minimizing a frequency-domain based cost function that produces monotonic convergence of the tracking error as a function of repetition number. Numerical illustrations show how the proposed single-model design method produces a repetitive controller in a single nominal model of the system.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.4 s.334
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• pp.45-52
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• 2005

This paper presents the characterization of through hole vias on printed circuit board (PCB) through the time domain and frequency domain measurements. The time domain measurement was performed on a single via using the TDR, and the model parameters were extracted by the fitting simulation using HSPICE. The frequency domain measurement was also performed by using 2 port VNA, and the model parameters were extracted by fitting simulation with ADS. Using the ABCD matrices, the do-embedding equations were derived probing in the same plane in the VNA measurement. Based on the single via characterization, the differential via characterization was also performed by using TDR measurements. The time domain measurements were performed by using the odd mode and even mode sources in TDR module, and the Parameter values were extracted by fitting with HSPICE. Comparing measurements with simulations, the maximum calculated differences were $14\%$ for single vias and $17\%$ for differential vias.

• Journal of the Korean Ceramic Society
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• v.26 no.1
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• pp.37-42
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• 1989

Periodic layered domain structures in doped LiNbO3 crystals grown by Czochralski method were obtained by thermal fluctuation and crystal rotation with inhomogeneous radial temprature distribution. The stressinduced domain formation mechanism model was suggested and discussed.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.867-878
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• 2021

In context awareness and user intention tasks, dataset construction is expensive because specific domain data are required. Although pretraining with a large corpus can effectively resolve the issue of lack of data, it ignores domain knowledge. Herein, we concentrate on data domain knowledge while addressing data scarcity and accordingly propose a multi-channel long short-term memory (LSTM). Because multi-channel LSTM integrates pretrained vectors such as task and general knowledge, it effectively prevents catastrophic forgetting between vectors of task and general knowledge to represent the context as a set of features. To evaluate the proposed model with reference to the baseline model, which is a single-channel LSTM, we performed two tasks: voice phishing with context awareness and movie review sentiment classification. The results verified that multi-channel LSTM outperforms single-channel LSTM in both tasks. We further experimented on different multi-channel LSTMs depending on the domain and data size of general knowledge in the model and confirmed that the effect of multi-channel LSTM integrating the two types of knowledge from downstream task data and raw data to overcome the lack of data.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1375-1385
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• 2022

In this paper, we propose a semi-supervised domain adaptation solution to deal with practical face recognition (FR) scenarios where a single face image for each target identity (to be recognized) is only available in the training phase. Main goal of the proposed method is to reduce the discrepancy between the target and the source domain face images, which ultimately improves FR performances. The proposed method is based on the Domain Adatation network (DAN) using an MMD loss function to reduce the discrepancy between domains. In order to train more effectively, we develop a novel loss function learning strategy in which MMD loss and cross-entropy loss functions are adopted by using different weights according to the progress of each epoch during the learning. The proposed weight adoptation focuses on the training of the source domain in the initial learning phase to learn facial feature information such as eyes, nose, and mouth. After the initial learning is completed, the resulting feature information is used to training a deep network using the target domain images. To evaluate the effectiveness of the proposed method, FR performances were evaluated with pretrained model trained only with CASIA-webface (source images) and fine-tuned model trained only with FERET's gallery (target images) under the same FR scenarios. The experimental results showed that the proposed semi-supervised domain adaptation can be improved by 24.78% compared to the pre-trained model and 28.42% compared to the fine-tuned model. In addition, the proposed method outperformed other state-of-the-arts domain adaptation approaches by 9.41%.

• Journal of Power Electronics
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• v.12 no.4
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• pp.623-631
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• 2012

In this paper, a digital controller design procedure is presented for single-phase voltage-doubler boost rectifiers (VDBR). The model derivation of the single-phase VDBR is performed in the s-domain. After that the simplified equivalent z-domain models are derived. These z-domain models are utilized to design the input current and the output dc-link voltage controllers. For the controller design in the z-domain, the traditional K-factor method is modified by considering the nature of the digital controller. The frequency pre-warping and anti-windup techniques are adapted for the controller design. By using the proposed method, the phase margin and the control bandwidth are accurately achieved as required by controller designers in a practical frequency range. The proposed method is applied to a 2.5 kVA single-phase VDBR for Uninterruptible Power Supply (UPS) applications. From the simulation and the experimental results, the effectiveness of the proposed design method has been verified.

• Journal of Magnetics
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• v.6 no.1
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• pp.36-41
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• 2001

A micromagnetic model and a single-domain model simulation programs were used to analyze the sensitivity of a $20\mu m\times 60\mu m \times 1000{\AA}$ permalloy strip as a magnetoresistance sensor with bias fields of various directions and magnitudes. The micromagnetic model agrees with the measured sensitivity data better than the single-domain model. The data show the highest peak sensitivity with the bias field at 90$^{\circ}$to the current. The peak sensitivity decreases and the peak broadens as the bias angle decreases. The simulation using the micromagnetic model shows that a bias angle smaller than 90$^{\circ}$eads to magnetization patterns which are free from closure domains or vertices over a wider range of bias fields.

• ETRI Journal
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• v.38 no.3
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• pp.487-493
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• 2016

Two new methods are proposed for an unsupervised adaptation of a language model (LM) with a single sentence for automatic transcription tasks. At the training phase, training documents are clustered by a method known as Latent Dirichlet allocation (LDA), and then a domain-specific LM is trained for each cluster. At the test phase, an adapted LM is presented as a linear mixture of the now trained domain-specific LMs. Unlike previous adaptation methods, the proposed methods fully utilize a trained LDA model for the estimation of weight values, which are then to be assigned to the now trained domain-specific LMs; therefore, the clustering and weight-estimation algorithms of the trained LDA model are reliable. For the continuous speech recognition benchmark tests, the proposed methods outperform other unsupervised LM adaptation methods based on latent semantic analysis, non-negative matrix factorization, and LDA with n-gram counting.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.07a
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• pp.1050-1053
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• 2001

There is great interest in developing magnetoresistance(MR) sensor, using ferromagnetic, electrically non-magnetic conducting and antiferromagnetic films, especially for the use in weak magnetic fields. Here, we report single and Wheatstone-bridge type of MR sensors made in Si(001)/HiO(300$\AA$)/NiFe bilayers. Angular dependence of MR profiles was measured in Si(001)/NiO(300$\AA$)/NiFe(450$\AA$) films as a function of an angle between current and applied field direction, also, linearity was determined. AMR characteristics of single MR sensors was well explained with single domain model. Good linearity in 45$^{\circ}$Wheatstone-bridge type of MR sensors consisting of 4 single MR sensors made in Si(001)/NiO(300$\AA$)/NiFe(450$\AA$) was shown in the range of about $\pm$50 Oe.