• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.4
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• pp.369-372
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• 2017

This paper presents a control scheme for three-level NPC inverters using small DC-link capacitors. To reduce the inverter system volume, the film capacitor with small capacitance is a promising candidate for the DC-link. When small capacitors are applied in a three level inverter, however, the AC ripple component increases in the DC-link NPV (neutral point voltage). In addition, the three-phase input grid currents are distorted when the DC-link capacitors are fed by diode rectifier. In this paper, the additional circuit is applied to compensate for small capacitor systems defect, and the offset voltage injection method is presented for the stabilization in NPV. These two proposed processes evidently ensure the quality improvement of the input grid currents and output load currents. The feasibility of the proposed method is verified by experimental results.

• Herbal Formula Science
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• v.28 no.3
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• pp.243-254
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• 2020

Objectives : Network pharmacology analysis is commonly used to investigate the synergies and potential mechanisms of multiple compounds by analyzing complex, multi-layered networks. We used TCMSP and BATMAN-TCM databases to compare results of network pharmacological analysis between White Ginseng(WG) and Red Ginseng(RG). Methods : WG and RG were compared with components and their target molecules using TCMSP database, and compound-target-pathway/disease networks were compared using BATMAN-TCM database. Results : Through TCMSP, 104 kinds of target molecules were derived from WG and 38 kinds were derived from RG. Using the BATMAN-TCM database, target pathways and diseases were screened, and more target pathways and diseases were screened compared to RG due to the high composition of WG ingredients. Analysis of component-target-pathway/disease network using network analysis tools provided by BATMAN-TCM showed that WG formed more networks than RG. Conclusions : Network pharmacology analysis can be effectively performed using various databases used in system biology research, and although the materials that have been reported in the past can be used efficiently for research on diseases related to targets, the results are unreliable if prior studies are focused on limited or narrow research areas.

• Speech Sciences
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• v.15 no.4
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• pp.135-146
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• 2008

Breath group generally refers to one of units of speech production. It is an integral component of structural and contextual features of utterances with some responsibility for fluctuations in speech intelligibility. The purpose of this study was to know the characteristics of breath group in reading passages spoken by healthy speakers, specifically in view of aerodynamic aspects. Eighteen female speakers aged from 20 to 30 years old without communication problems and in healthy condition were participated in this study. PAS (Phonatory Aerodynamic System) was used for aerodynamic measurement of breath group. Results showed that the mean value of breath group in reading tasks was 16.03 per minute (SD=3.1), and the spoken syllables per one breath group were 17.95. And the mean time (m) of breath group was 3.06 (SD=0.62), and the ratio of exhalation and inhalation was appeared in the 1:5. The results need to be discussed in values of normality of breath group and clinical viewpoint, especially their potential implication from speech intelligibility caused by brain damage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.3
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• pp.522-538
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• 2013

Content based image retrieval has become an increasingly important research topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The retrieval systems rely on a key component, the predefined or learned similarity measures over images. We note that, the similarity measures can be potential improved if the data distribution information is exploited using a more sophisticated way. In this paper, we propose a similarity measure learning approach for image retrieval. The similarity measure, so called Fisher kernel, is derived from the probabilistic distribution of images and is the function over observed data, hidden variable and model parameters, where the hidden variables encode high level information which are powerful in discrimination and are failed to be exploited in previous methods. We further propose a discriminative learning method for the similarity measure, i.e., encouraging the learned similarity to take a large value for a pair of images with the same label and to take a small value for a pair of images with distinct labels. The learned similarity measure, fully exploiting the data distribution, is well adapted to dataset and would improve the retrieval system. We evaluate the proposed method on Corel-1000, Corel5k, Caltech101 and MIRFlickr 25,000 databases. The results show the competitive performance of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1400-1420
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• 2012

Object detection and tracking using visual sensors is a critical component of surveillance systems, which presents many challenges. This paper addresses the enhancement of object detection and tracking via the combination of multiple visual sensors. The enhancement method we introduce compensates for missed object detection based on the partial detection of objects by multiple visual sensors. When one detects an object or more visual sensors, the detected object's local positions transformed into a global object position. Local and global information exchange allows a missed local object's position to recover. However, the exchange of the information may degrade the detection and tracking performance by incorrectly recovering the local object position, which propagated by false object detection. Furthermore, local object positions corresponding to an identical object can transformed into nonequivalent global object positions because of detection uncertainty such as shadows or other artifacts. We improved the performance by preventing the propagation of false object detection. In addition, we present an evaluation method for the final global object position. The proposed method analyzed and evaluated using case studies.

• Communications of Mathematical Education
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• v.29 no.2
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• pp.197-214
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• 2015

This study is to design Flipped Learning classrooms of learner-centered education on the pre-service math teachers education. The study aims to explore the feasibility of teaching and learning method. To achieve the objectives of the study was to explore the teaching and learning model. Flipped learing classroom design includes a main step of a typical process of teaching system. And we designed the model based on the ADDIE Model. This model contains the design steps and the Flipped learning component of the teaching and learning design model. Designed classroom presented in three steps that are before classroom, during classroom and after classroom.

• World Technopolis Review
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• v.4 no.3
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• pp.144-156
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• 2015

Globalization and knowledge-based economy have increased the importance of local areas as the units of global competition. Therefore, the meaning of localities has been emphasized as the core value of economic activities. In this context, innovation cluster has been recognised and emphasized as effective policy measure for innovation. Therefore, most countries have been trying to develop innovation clusters with their expectation for a rapid growth of economy. Nevertheless, there have been minimal empirical researches on innovation cluster. Therefore, for suggesting implications that activation factors of innovation cluster are to have an effect on tenant's business activities, this study conducted a literature review for the theories of regional innovation system(RIS) and innovation cluster. As a result, the activation factors of innovation cluster were classified into institutional, physicals, and social factor. The case of Gyeonggi province's innovation cluster policy was examined for an empirical analysis. Data were analyzed using ordered logistic regression. The results were as follows:First, Institutional and Infra factors had a positive influence on firms' business activities in every empirical test, so they were the most important activation factors of innovation cluster. Second, regarding the interactive effects of financial support, the interactive effects between financial support and Infra factor had a positive influence on the firms' business activities, according to the result of the empirical test.

• 한국공간정보시스템학회:학술대회논문집
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• 2003.11a
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• pp.84-90
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• 2003

최근 이동 컴퓨팅 기술이 급속도로 발전하면서 이동 객체의 위치정보를 활용한 위치 찾기 서비스, 교통 정보 서비스, 긴급 구조 서비스, 모바일 광고 서비스와 같은 위치 기반 서비스가 부각되고 있다. 이와 같은 다양한 서비스를 제공하기 위해서는 이동 객체의 위치정보를 신속하게 저장, 검색, 갱신할 수 있는 이동 객체 데이타베이스 시스템이 필수적으로 요구된다. 그러나, 기존의 데이타베이스 시스템을 사용할 경우에는 저장 공간을 많이 차지게 되고, 불필요한 트랜잭션 연산으로 인하여 대용량의 위치 데이타 관리에 큰 오버헤드가 발생한다는 문제가 있다. 그러므로, 이동 객체의 위치 데이타를 저장하고 관리하기 위하여 화일 기반의 저장 시스템을 사용하는 것이 보다 더 효율적이다. 이에 본 논문에서는 대용량의 위치 데이타를 효과적으로 저장 및 검색할 수 있는 화일 기반 이동 객체 저장 컴포넌트를 설계하고 구현하였다. 화일 기반 이동 객체 저장 컴포넌트는 다중 연결 관리자, 단순 질의 처리기, 메타데이타 관리자, 데이타 화일 관리자, 인덱스 화일 관리자, 로그 관리자, 관리툴로 구성된다.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.4
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• pp.27-33
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• 2013

In this study, the FMEA and FTA for reliability analysis of hybrid rocket motor are performed, that was designed in the Hybrid Rocket Propulsion Laboratory of Korea Aerospace University. In order to carry out these analyses the structure of the hybrid rocket motor is hierarchically divided into 36 parts down to the component level and FMEA is carried out with 72 failure modes. Reliability is assessed based on the FMEA, and the results are used in the FTA to evaluate the overall system reliability. In the FMEA, the relationship between the cause and failure modes, effects and their risk priorities are evaluated qualitatively. 27 failure modes are chosen as those with the critical severity that should be improved with priority. As a result of the FMEA / FTA study, a series of design or material changes are made for the improvement of reliability.

• Analytical Science and Technology
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• v.33 no.2
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• pp.86-97
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• 2020

Reconstruction and separation of explosive-contaminated overlapping fingerprints constitutes an analytical challenge of high significance in forensic sciences. Laser-induced breakdown spectroscopy (LIBS) allows real-time chemical mapping by detecting the light emissions from laser-induced plasma and can offer powerful means of fingerprint classification based on the chemical components of the sample. During recent years LIBS has been studied one of the spectroscopic techniques with larger capability for forensic sciences. However, despite of the great sensitivity, LIBS suffers from a limited detection due to difficulties in reconstruction of overlapping fingerprints. Here, the authors propose a simple, yet effective, method of using chemical mapping to separate and reconstruct the explosive-contaminated, overlapping fingerprints. A Q-switched Nd:YAG laser system (1064 nm), which allows the laser beam diameter and the area of the ablated crater to be controlled, was used to analyze the chemical compositions of eight samples of explosive-contaminated fingerprints (featuring two sample explosive and four individuals) via the LIBS. Then, the chemical validations were further performed by applying the Raman spectroscopy. The results were subjected to principal component and partial least-squares multivariate analyses, and showed the classification of contaminated fingerprints at higher than 91% accuracy. Robustness and sensitivity tests indicate that the novel method used here is effective for separating and reconstructing the overlapping fingerprints with explosive trace.