• 전력전자학회:학술대회논문집
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• 전력전자학회 2002년도 전력전자학술대회 논문집
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• pp.585-588
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• 2002

In this paper, the current controlled active poler filter(APF) with the performance of reducing harmonic and improving power factor is studied. It has high speed and good performance with low cost. The current controlled shunt APF is proposed, and the control part of APF is designed of SOC(System On Chip). So this system has low expense and good performance. In this study, the micro-controller which designed with VHDL. is applied to APF system. And the proposed technique in this paper demonstrates the excellent of the dedicated micro-controller. VHDL-based ASIC can simplify the process of development and has a competition in market because it reduces the consuming time for the design of IC(Integrated Circuit) in system level.

• Journal of Korean Vacuum Science & Technology
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• 제3권1호
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• pp.66-73
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• 1999

In this paper, the design of one-chip FED system integrated with driving circuits in reported on the basis of MOSFET controlled FEA (MCFEA). To integrate a MOSFET with a FEA efficiently, a new fabrication process is proposed. It is confirmed that the MOSFET with threshold voltage of about 2volts controls the FEA emission current up to 20 ${\mu}$A by applying driving voltage of 15 volts, which is enough current level to utilize the MCFEA as a pixel for FED. The drain breakdown voltage of the MOSFET is measured to be 70 volts, which is also high enough for 60 volt operation of FED. The circuits for row and column driver are designed stressing on saving area, reducing malfunction probability and consuming low power to maximize the merit of on-chip driving circuits. Dynamic logic concept and bootstrap capacitors are used to meet these requirements. By integrating the driving circuit with FEA, the number of external I/O lines can be less than 20, irrespectively of the number of pixels.

• Journal of Biosystems Engineering
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• 제40권3호
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• pp.277-283
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• 2015

Background: Foodborne disease outbreaks from various food sources are a major health concern worldwide. Current methods for detection of foodborne pathogens are both expensive and time-consuming. Purpose: This review aims to present the current information available on the use of lateral flow test strips to detect pathogens in food products to enhance food safety. Results: Frequent foodborne disease outbreaks from various food sources have increased the need for rapid and easy methods for routine analysis of foodborne pathogens. Present detection methods for foodborne pathogens require expensive instruments, experts, and long time for sample analysis. Lateral flow test strips have drawn attention in recent years because of their ability to detect analytes quickly and easily. This review focuses on the principle of the lateral flow test, the various formats of lateral flow test strips, recognition elements, labeling tags, and reading instruments. In addition, this review also discusses the future prospects for the lateral flow test strips.

• 한국멀티미디어학회논문지
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• 제22권4호
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• pp.432-442
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• 2019

Most current human action recognition methods based on deep learning methods. It is required, however, a very high computational cost. In this paper, we propose an action change detection method to reduce repetitive human action recognition tasks. In reality, simple actions are often repeated and it is time consuming process to apply high cost action recognition methods on repeated actions. The proposed method decides whether action has changed. The action recognition is executed only when it has detected action change. The action change detection process is as follows. First, extract the number of non-zero pixel from motion history image and generate one-dimensional time-series data. Second, detecting action change by comparison of difference between current time trend and local extremum of time-series data and threshold. Experiments on the proposed method achieved 89% balanced accuracy on action change data and 61% reduced action recognition repetition.

• Clinical and Experimental Pediatrics
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• 제64권9호
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• pp.436-442
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• 2021

This article aimed to summarize the impact and burden of pediatric postintensive care syndrome (PICS-p) in the physical, mental, cognitive, and social health domains after a review of the current pediatric literature in MEDLINE and PubMed. We also aimed to elucidate the limitations of the current evaluation tools used in limited-resource settings. PICS-p can impact a child's life for decades. Most validated tools are time-consuming, require qualifications, and expertise, are often limited to older children, and can evaluate only one domain. A novel, simple, and comprehensive surveillance tool can aid healthcare providers in the early detection and intervention of PICS-p. Further studies should validate and refine the parameters that will enhance the outcomes of pediatric intensive care unit survivors.

• International Journal of Internet, Broadcasting and Communication
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• 제14권3호
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• pp.149-154
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• 2022

In recent years, the application of deep learning method to computer vision has shown to achieve great performances. Thus, many research projects have also applied deep learning technology to railroad defect detection. In this paper, we have reviewed the researches that applied computer vision based deep learning method to railroad defect detection and inspection, and have discussed the current trend and the direction of those researches. Many research projects were targeted to operate automatically without visual inspection of human and to work in real-time. Therefore, methods to speed up the computation were also investigated. The reduction of the number of learning parameters was considered important to improve computation efficiency. In addition to computation speed issue, the problem of annotation was also discussed in some research projects. To alleviate the problem of time consuming annotation, some kinds of automatic segmentation of the railroad defect or self-supervised methods have been suggested.

• 한국정밀공학회지
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• 제12권1호
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• pp.22-28
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• 1995

Micro Drills have found ever wider application. However micro drilling is a machining to integrate the difficult machinablities such as tool stiffness, position control and revolution accuracy, and is known to cost and time consuming. So, this study aimed to practice ultraminiature drilling(0.05 .phi. ) wiht simple component, if possible. System is developed as the three modules : feed drives, spindle and monitoring part. The dynamics of measured current signals from the spindle of Micro Hole Drilling machine are investigated to establish the criteria of stepfeed mechanism. Cutting experiments identify the relationship of spindle rpm, feed rate and tool life. The smaller drill diameter is, the more suitable cutting condition have to be selected because of chip packing.

• 한국지하수토양환경학회지:지하수토양환경
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• 제22권2호
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• pp.17-25
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• 2017

The efficiency and mechanism of electrochemical phenol oxidation using persulfate (PS) and nanosized zero-valent iron (NZVI) were investigated. The pseudo-first-order rate constant for phenol removal by the electrochemical/PS/NZVI ($1mA^*cm^{-2}/12$ mM/6 mM) process was $0.81h^{-1}$, which was higher than those of the electrochemical/PS and PS/NZVI processes. The electrochemical/PS/NZVI system removed 1.5 mM phenol while consuming 6.6 mM PS, giving the highest stoichiometric efficiency (0.23) among the tested systems. The enhanced phenol removal rates and efficiencies observed for the electrochemical/PS/NZVI process were attributed to the interactions involving the three components, in which the electric current stimulated PS activation, NZVI depassivation, phenol oxidation, and PS regeneration by anodic or cathodic reactions. The electrochemical/PS/NZVI process effectively removed phenol oxidation products such as hydroquinone and 1,4-benzoquinone. Since the electric current enhances the reactivities of PS and NZVI, process performance can be optimized by effectively manipulating the current.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권10호
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• pp.1259-1265
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• 2004

분류학습에서 높은 정확도를 유지하기 위해서는 충분한 분류 데이타가 필요하게 되는데 분류 데이타는 미 분류 데이타보다 생성하기가 어려운 경우가 많다. 따라서 미 분류 데이타를 활용하여 분류의 정확도를 향상시키는 것은 큰 효용성을 가지며 이러한 미 분류 데이타를 활용하는 대표적인 학습방법 중의 하나는 협력학습(co-training) 알고리즘이다. 이는 데이타를 두 개의 독립적인 속성그룹으로 나누어 두개의 분류자로 학습한 후 미 분류 데이타를 분류하고 그중 가장 신뢰성이 높은 데이타를 분류 데이터에 포함하고 이를 반복하는 학습모델이다. 하지만 이 방법은 전체 데이타의 속성을 독립적인 두개의 집합으로 분할하여야하는 제약이 있다. 따라서 본 연구에서는 이와 같은 문제점을 개선하여 보통의 데이터베이스에 적용시킬 수 있는 새로운 협력학습방법을 제시 하고자한다. 즉. 두 개의 독립적인 속성 그룹으로 나누는 가정을 따르지 않고 전체 속성을 사용할 수 있으며 두 개 이상의 분류자를 사용하는 새로운 협력학습방법을 제안하였다.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2008년도 정보통신설비 학술대회
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• pp.414-417
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• 2008

This paper presents the design and analysis of 2.45GHz Low-IF Mixer using CMOS 0.18um. The Mixer is implemented by using the Gilbert-type configuration, current bleeding technique, and the resonating technique for the tail capacitance. And the design of this Double Balance Mixer is based on its lineaity since it is important in the interference cancellation system. The low flicker noise mixer is implemented by incorporating a double balanced Gilber-type configuration, the RF leakage-less current bleeding technique, and Cp resonating technique. The proposed mixer has a simulated conversion gain of 16dB a simulated IIP3 of -3.3dBm and P1dB is -19dBm. A simulated noise figure of 6.9dB at l0MHz and a flicker corner frequency of 510kHz while consuming only 10.65mW od DC power. The layout of Mixer for one-chip design in a 0.18-um TSMC process has 0.474mm$\times$0.39 mm size.