• Journal of the Korean Society for Precision Engineering
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• v.26 no.3
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• pp.40-46
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• 2009

Toroidally-wound brushless direct-current (BLOC) machines are compact, highly efficient, and can work across a large magnetic gap. For these reasons, they have been used in pumps, flywheel energy storage systems and left ventricular assist devices among others. The common feature of these systems is a spinning rotor supported by a set of (either mechanical or magnetic) bearings. From the view point of dynamics, it is desirable to increase the first critical speed of the rotor so that it can run at a higher operating speed. The first critical speed of the rotor is determined by the radial stiffnesses of the bearings and the rotor mass. The motor also affects the first critical speed if the rotor is displaced from the rotating center. In this paper, we analytically derive the flux density distribution in a toroidally-wound BLOC machine and also derive the negative stiffness of the motor, based on the assumption that the rotor displacement perturbs the flux density distribution linearly. The estimated negative stiffness is validated by finite element analyses.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1551-1564
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• 2016

The high penetration level of inverter-based distributed generation (DG) power plants is challenging the low-voltage ride-through requirements, especially under unbalanced voltage sags. Recently, a flexible injection of both positive- (PS) and negative-sequence (NS) reactive currents has been suggested for the next generation of grid codes. This can enhance the ancillary services for voltage support at the point of common coupling (PCC). In light of this, considering distant grid faults that occur in a mainly inductive grid, this paper proposes a complete voltage support control scheme for the interface inverters of medium or high-rated DG power plants. The first contribution is the development of a reactive current reference generator combining PS and NS, with a feature to increase the PS voltage and simultaneously decrease the NS voltage, to mitigate voltage imbalance. The second contribution is the design of a voltage support control loop with two flexible PCC voltage set points, which can ensure continuous operation within the limits required in grid codes. In addition, a current saturation strategy is also considered for deep voltage sags to avoid overcurrent protection. Finally, simulation and experimental results are presented to validate the effectiveness of the proposed control scheme.

• Korean Journal of Human Ecology
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• v.17 no.4
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• pp.639-648
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• 2008

This study is to examine the meaning of death, the level of death anxiety, and the aspect of death anxiety that the aged have. For this, a quantitative research subjecting 532 of the aged living in local area, Jeollabuk-do was carried out. And among those 532 questionnaires, 10 were subjected for depth interview. The following is a summary of the result from this study. First, the meaning of death for the aged is classified into three classes as positive, neutral and negative meaning. Among these, there were far greater numbers of the aged who put neutral or negative meanings on their death than the positive one. Second, death anxiety of the aged are divided into three factors: 'annihilation anxiety', 'process anxiety', and 'afterdeath anxiety'. The factor that involves death anxiety the most was process anxiety, then afterdeath anxiety, and annihilation anxiety, in the order. Third, as a result of classifying the feature of death anxiety in the aged into the symptoms of death anxiety and the motive of recognizing death anxiety. Death anxiety is classified into the people with symptoms and those without symptoms, and those with certain symptoms are classified into the physical symptoms and the mental symptoms. The motive of recognizing death anxiety appeared when the individual is aged, experiences the death of other people, suffers physical pains, and when there is a mental loneliness.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.175-186
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• 2004

We present a hybrid approach of texture-based method and connected component (CC)-based method for text extraction in complex images. Two primary methods, which are mainly utilized in this area, are sequentially merged for compensating for their weak points. An automatically constructed MLP-based texture classifier can increase recall rates for complex images with small amount of user intervention and without explicit feature extraction. CC-based filtering based on the shape information using NMF enhances the precision rate without affecting overall performance. As a result, a combination of texture and CC-based methods leads to not only robust but also efficient text extraction. We also enhance the processing speed by adopting appropriate region marking methods for each input image category.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.95-102
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• 2012

Interactive drama is a story which requires user's free choice and participation. In this study, we grasp user's preference by making training data that utilize characters of interactive drama. Furthermore, we describe process of implementing systems which recommend new users path of stories that correspond with their preference. We used PCA and NMF to extract characteristic of preference. The success rate of recommending was 75% with PCA, while 62.5% with NMF.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1412-1417
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• 2004

Sparse coding or independent component analysis (ICA) which is a holistic representation, was successfully applied to elucidate early auditor${\gamma}$ processing and to the task of sound classification. In contrast, parts-based representation is an alternative way o) understanding object recognition in brain. In this thesis we employ the non-negative matrix factorization (NMF) which learns parts-based representation in the task of sound classification. Methods of feature extraction from the spectro-temporal sounds using the NMF in the absence or presence of noise, are explained. Experimental results show that NMF-based features improve the performance of sound classification over ICA-based features.

• Journal of Powder Materials
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• v.25 no.6
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• pp.507-513
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• 2018

This study investigates the viability of using a Na-ion battery with a tin(Sn) anode to mitigate the vulnerability caused by volume changes during discharge and charge cycling. In general, the volume changes of carbon material do not cause any instability during intercalation into its layer structure. Sn has a high theoretical capacity of $847mAh\;g^{-1}$. However, it expands dramatically in the discharge process by alloying Na-Sn, placing the electrode under massive internal stress, and particularly straining the binder over the elastic limit. The repeating strain results in loss of active material and its electric contact, as well as capacity decrease. This paper expands the scope of fabrication of Na-ion batteries with Sn by fabricating the binder as an auxetic structure with a unique feature: a negative Poisson ratio (NPR), which increases the resistance to internal stress in the Na-Sn alloying/de-alloying processes. Electrochemical tests and micrograph images of auxetic and common binders are used to compare dimensional and structural differences. Results show that the capacity of an auxetic-structured Sn electrode is much larger than that of a Sn electrode with a common-structured binder. Furthermore, using an auxetic structured Sn electrode, stability in discharge and charge cycling is obtained.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.647-658
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• 2021

Analysts' forecasts are important for providing useful guidance to investors, especially individual or small investors, and therefore it becomes critical to identify the elements which can potentially increase errors in analysts' forecasts. This study investigates potential factors which can lead to errors in forecasting by analysts, specifically in terms of the level and attributes of corporate earnings. Utilizing a sample of firms listed on the Korean stock markets, this study provides evidence that firms with more volatile and unpredictable earnings feature less accurate analyst forecasts. This study fills a void in the literature by conducting empirical tests for earnings attributes in terms of volatility and unpredictability that could potentially undermine the forecast accuracy. The negative association between the quality of earnings and forecast accuracy is more pronounced for firms with negative net income values. Additional analysis demonstrates that forecast accuracy is significantly lower for the fourth quarter than for other fiscal quarters and that fourth quarter earnings tend to be more volatile and unpredictable. This study contributes to the literature by providing new empirical evidence regarding the comprehensive effects of earnings quality and level on analysts' forecasting accuracy and further suggests potential factors contributing to the fourth quarter anomaly in analyst forecasts in terms of earnings attributes.

• The Journal of Industrial Distribution & Business
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• v.9 no.2
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• pp.47-55
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• 2018

Purpose - To meet the needs of various customers in an uncertain market environment, many companies use product modularization strategies. Modularization of a product means that one product consists of several components and that the type of product can be changed according to the combination of components. The greatest feature of modularity is that changes in one component do not significantly affect the physical changes in the other component to which they are connected. Modularization of products is recognized as a very important strategy to reflect increasingly complicated customer requirements to products and respond to the needs of various markets. Many studies have been made in connection with the concept of mass customer satisfaction. There are many prior studies that modularization of such products positively affects the operational performance (manufacturing cost, fast delivery, etc.) and innovation of the product. However, excessive modularization has been found to have a negative effect on this performance. However, there are very few studies on the nonlinear relationship between product modularization and customer satisfaction. Supplementing these academically insufficient parts is very necessary when considering the current market environment. Research design, data, and methodology - In order to make up for the shortcomings of academic research in Korea, this study collects data through questionnaires in electronic, auto, and defense industry. This is because these industries are using modularity of products. based on lots of previous studies and information overload theory, we made two hypothesis and verify with empirical analysis. All 108 data were used. We used the R program and SPSS program for statistical verification. Results - As a result of the study, modularization of products showed positive relationship with customer satisfaction to a certain level. However, it has been found that when the modularization is over and beyond a certain level, there is a negative relationship with customer satisfaction. Conclusions - Excessive modularization of products can have a negative impact on customer satisfaction. This result can be understood as a result of human limited rationality due to information overload. Therefore, it is important for companies to apply appropriate modularity to product design.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3925-3932
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• 2013

Emotion is closely related to the life of human, so has effect on many parts such as concentration, learning ability, etc. and makes to have different behavior patterns. The purpose of this paper is to extract important features based on physiological signals to recognize negative emotion. In this paper, after acquisition of electrocardiography(ECG), electroencephalography(EEG), skin temperature(SKT) and galvanic skin response(GSR) measurements based on physiological signals, we designed an accurate and fast algorithm using combination of linear discriminant analysis(LDA) and genetic algorithm(GA), then we selected important features. As a result, the accuracy of the algorithm is up to 96.4% and selected features are Mean, root mean square successive difference(RMSSD), NN intervals differing more than 50ms(NN50) of heart rate variability(HRV), ${\sigma}$ and ${\alpha}$ frequency power of EEG from frontal region, ${\alpha}$, ${\beta}$, and ${\gamma}$ frequency power of EEG from central region, and mean and standard deviation of SKT. Therefore, the features play an important role to recognize negative emotion.