• Journal of Power Electronics
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• 제1권1호
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• pp.26-35
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• 2001

In most inverter/converter applications SVPWM method is a preferred approach since it shows good characteristics in linear modulation range and waveform quality. In this paper, we propose a new carrier based SVPWM method for multi-level system, First, we survey the conventional carrier based SVPWM method, and investigate the problem of the conventional one for the multi-level system with the focus on the switching frequency harmonic flux trajectories. Finally, we propose a new carrier based SVPWM method that can reduce harmonic distortion. Simulation and experimental results are given for verification of the proposed SVPWM method.

• ETRI Journal
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• 제43권3호
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• pp.511-523
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• 2021

The World Health Organization provides guidelines for managing the particulate matter (PM) level because a higher PM level represents a threat to human health. To manage the PM level, a procedure for measuring the PM value is first needed. We use a PM sensor that collects the PM level by laser-based light scattering (LLS) method because it is more cost effective than a beta attenuation monitor-based sensor or tapered element oscillating microbalance-based sensor. However, an LLS-based sensor has a higher probability of malfunctioning than the higher cost sensors. In this paper, we regard the overall malfunctioning, including strange value collection or missing collection data as anomalies, and we aim to detect anomalies for the maintenance of PM measuring sensors. We propose a novel architecture for solving the above aim that we call the hypothesis pruning generative adversarial network (HP-GAN). Through comparative experiments, we achieve AUROC and AUPRC values of 0.948 and 0.967, respectively, in the detection of anomalies in LLS-based PM measuring sensors. We conclude that our HP-GAN is a cutting-edge model for anomaly detection.

• 가정∙방문간호학회지
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• 제11권1호
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• pp.33-43
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• 2004

Purpose: This study is a descriptive research conducted for looking into the role awareness level. role conflicts, and job satisfaction among professional home care nurses in the field of hospital based home care nursing service. Method: 154 specialized home care nurses in 63 hospitals and clinics that are implementing home care programs were subject to the study. Result: 1. The level of role awareness among professional home care nurses was $4.47\pm0.41$ on average out of 5. 2. The average score for role conflicts was $3.87\pm0.61$ out of 5. 3. In terms of job satisfaction level. $3.33\pm0.71$ was scored out of 5. 4. It has been discovered that there are statistically significant positive correlations among role awareness level, role conflicts(r= .224, P= .005), and job satisfaction level(r= .166, P=.040), while a negative correlation was detected between role conflicts and job satisfaction level(r=-.210, P= .009). Conclusion: The level of role awareness among professional home care nurses in the field of hospital based home care nursing service was very high and job satisfaction level was high when the level of home care nursing antecedents was high and the organization structure of working place was independent. But the level of role conflicts coming out of the weakness of job-supporting system was high. So the realistic alternative such as the improvement of working environment by administrative, institutional support, is required to make up for this problem in the future.

• Human Ecology Research
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• 제60권3호
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• pp.331-344
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• 2022

The purpose of this study was to identify a support method for the introduction of metaverse-based classes (MBC) in home economics (HE) education. This was achieved by diagnosing the stages of concern and levels of use exhibited by HE teachers applying the concerns-based adoption model (CBAM). Questionnaires were sent to a convenience sample of middle- and high-school HE teachers using the KSDC (Korea Social Science Data Center). Overall, 271 responses were received, and the data were analyzed using KSDC E-STAT 3.0 and SPSS 28.0.1.1. The results were as follows: First, regarding the level of knowledge of MBC, the introductory level was the most common (139 respondents, 51.3%,), followed by the beginner level (81, 29.9%), the intermediate level (28, 10.3%,), the advanced level (12, 4.4%), and the master level (11, 4.1%). Average responses on a 5-point Likert scale to questions about the use of metaverse in HE classes were as follows: possibility (4.02), necessity (3.82), and usefulness (3.90). Second, HE teachers' stages of concern in MBC were as follows (in descending order): unconcerned - stage 0, and information - stage 1 (86.9), personal - stage 2 (85.6), management - stage 3 (80.9), collaboration - stage 5 (57.5), consequence - stage 4 (57.4), and refocusing - stage 6 (55.2). Third, the use of MBC was highest for orientation - level 1 (173 respondents, 63.8%), followed by non-use - level 0 (34, 12.5%), preparation - level 2 (29, 10.7%), mechanical - level 3 (15, 5.5%), refinement - level 5 (8, 3.0%), renewal - level 7 (8, 3.0%), routine - level 4 (3, 1.1%), and integration - level 6 (1, 0.4%). Many HE teachers had heard about MBC but were in the introductory level of not knowing what it is, and at the stage of being unconcerned or wanting to know about MBC. Of the 271 respondents, only 35 used metaverse in classes. Therefore, it is necessary to provide teacher training opportunities that provide basic information on the significance and implementation of MBC for HE teachers. Also, an MBC guideline book should be developed and distributed to HE teachers. Finally, a teacher community meeting is needed to share the expertise of teachers with substantial experience in using MBC.

• Journal of Computing Science and Engineering
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• 제9권4호
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• pp.204-213
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• 2015

Under the conditional independence assumption among local features, the Naive Bayes Nearest Neighbor (NBNN) classifier has been recently proposed and performs classification without any training or quantization phases. While the original NBNN shows high classification accuracy without adopting an explicit training phase, the conditional independence among local features is against the compositionality of objects indicating that different, but related parts of an object appear together. As a result, the assumption of the conditional independence weakens the accuracy of classification techniques based on NBNN. In this work, we look into this issue, and propose a novel Bayesian network for an NBNN based classification to consider the conditional dependence among features. To achieve our goal, we extract a high-level feature and its corresponding, multiple low-level features for each image patch. We then represent them based on a simple, two-level layered Bayesian network, and design its classification function considering our Bayesian network. To achieve low memory requirement and fast query-time performance, we further optimize our representation and classification function, named relation-based Bayesian network, by considering and representing the relationship between a high-level feature and its low-level features into a compact relation vector, whose dimensionality is the same as the number of low-level features, e.g., four elements in our tests. We have demonstrated the benefits of our method over the original NBNN and its recent improvement, and local NBNN in two different benchmarks. Our method shows improved accuracy, up to 27% against the tested methods. This high accuracy is mainly due to consideration of the conditional dependences between high-level and its corresponding low-level features.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2007년도 정기 학술대회 논문집
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• pp.157-162
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• 2007

A new level set based topology optimization employing inner-front creation algorithm is presented. In the conventional level set based topology optimization, the optimum topology strongly depends on the initial level set distribution due to the incapability of inner-front creation during optimization process. In the present work, in this regard, an inner-front creation algorithm is proposed. in which the sizes. shapes. positions, and number of new inner-fronts during the optimization process can be globally and consistently identified by considering both the value of a given criterion for inner-front creation and the occupied volume (area) of material domain. To facilitate the inner-front creation process, the inner-front creation map which corresponds to the discrete valued criterion of inner-front creation is applied to the level set function. In order to regularize the design domain during the optimization process, the edge smoothing is carried out by solving the edge smoothing partial differential equation (PDE). Updating the level set function during the optimization process, in the present work, the least-squares finite element method (LSFEM) is employed. As demonstrative examples for the flexibility and usefulness of the proposed method. the level set based topology optimization considering lightweight design of 3D shell structure is carried out.

• Journal of Electrical Engineering and Technology
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• 제11권4호
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• pp.1035-1041
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• 2016

Internal cracks in products are invisible and can lead to fatal crashes or damage. Since X-rays can penetrate materials and be attenuated according to the material’s thickness and density, they have rapidly become the accepted technology for non-destructive inspection of internal cracks. This paper presents a robust crack filter based on local gray level variation and multiscale analysis for automatic detection of cracks in X-ray images. The proposed filter takes advantage of the image gray level and its local variations to detect cracks in the X-ray image. To overcome the problems of image noise and the non-uniform intensity of the X-ray image, a new method of estimating the local gray level variation is proposed in this paper. In order to detect various sizes of crack, this paper proposes using different neighboring distances to construct an image pyramid for multiscale analysis. By use of local gray level variation and multiscale analysis, the proposed crack filter is able to detect cracks of various sizes in X-ray images while contending with the problems of noise and non-uniform intensity. Experimental results show that the proposed crack filter outperforms the Gaussian model based crack filter and the LBP model based method in terms of detection accuracy, false detection ratio and processing speed.

• 한국국방경영분석학회지
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• 제28권2호
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• pp.1-19
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• 2002

This study shows the effect of inventory policy change from supplier-based to customer-based. We focus on the service level, cost, and information distortion of the Military Supply Chain(MSC) with System Dynamics. We design MSC model according to field practician interviews by using Vensim. The simulation makes a comparison between supply-based inventory policy performances and order-based inventory policy performances. In order to evaluate the MSC performances, we measure the accumulation of backlog(service level), supply chain cost, and order percentage overshoot(information distortion). The results show that 1) changing inventory policy from supplier-based to end customer order-based gets a good customer service, reduces MSC cost, and prevents information distortion, 2) changing inventory policy from supplier-based to immediate customer order-based reduces a small amount of MSC cost and deteriorates customer service, and 3) supply level is main factor for MSC performances improvement. This study implicates the policy change makes a improvement of MSC performance without introducing information system.

• 한국지진공학회논문집
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• 제20권3호
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• pp.181-190
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• 2016

The objective of this study is to apply performance-based seismic design to high-rise apartment buildings in Korean considering collapse prevention level. The possible issues during its application were studied and the suggestions were made based on the findings from the performance-based seismic design of a building with typical residential multi-unit layout. The lateral-force-resisting system of the building is ordinary shear walls system with a code exception of height limit. In order to allow the exception, the serviceability and the stability of the ordinary shear wall structure need to be evaluated to confirm that it has the equivalent performance as the one designed under the Korean Building Code 2009. The structure was evaluated whether it satisfied its performance objectives to withstand Service Level and Maximum Considered Earthquake.

• The Journal of Asian Finance, Economics and Business
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• 제8권12호
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• pp.363-370
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• 2021

This study aims to revisit the issues and misconceptions about financial inclusion (FI) indices. For indices construction, this study uses two approaches: one approach following the methodology of Sarma (2008) which is based on UNDP methodology, while the other is the Dynamic Factor Model (DFM)-based index of Stock and Watson (2002) and Rehman et al. (2021). The data of 18 economies of Asia from 1997 till 2017 is used for indices construction and analysis. The authors constructed macro and micro-level financial inclusion indices based on the different types of financial inclusion indicators. Second, the authors have critically evaluated two different approaches, and the results show that Sarma (2008)-based index show financial inclusion's level, while DFM-based index reveal fluctuation in the current year's financial inclusion level due to the prior variations. For measuring the level of financial inclusion, the Sarma (2008) index is effective, while for forecasting the level of financial inclusion, the DFM approach is more appropriate. Furthermore, the micro and macro aspects of financial inclusion should be reflected in separate indices for better understanding and in-depth insights.