• 한국산업융합학회 논문집
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• 제26권2_1호
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• pp.225-230
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• 2023

This research addresses sound command based human tracking problems for autonomous cleaning mobile robot in a networked AI space. To solve the problem, the difference among the traveling times of the sound command to each of three microphones has been used to calculate the distance and orientation of the sound from the cleaning mobile robot, which carries the microphone array. The cross-correlation between two signals has been applied for detecting the time difference between two signals, which provides reliable and precise value of the time difference compared to the conventional methods. To generate the tracking direction to the sound command, fuzzy rules are applied and the results are used to control the cleaning mobile robot in a real-time. Finally the experiment results show that the proposed algorithm works well, even though the mobile robot knows little about the environment.

• 대한방사선기술학회지:방사선기술과학
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• 제43권1호
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• pp.1-7
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• 2020

In this study, the contamination level was measured using an ATP meter using adenosine triphosphate bioluminescent material to find effective infection control to compensate for the disadvantages of the microbial culture method used for hygiene control of ultrasound probe. The convex probes were selected from six ultrasound probe in the hospital, and the samples were taken in real time before and after cleaning to check the contamination of the probe. In order to classify the pollution degree using the APT meter was classified by category. A total of 78 samples were collected from the ultrasound probe. When the pollution levels before and after cleaning were classified by category, 76.6% of the samples were classified into category 3·4 before cleaning, but they decreased to 23.3% after cleaning. 13.3% before cleaning was in category 1, but increased to 43.3% after cleaning. By classifying the pollution level, it was confirmed that the pollution level was significantly reduced by category. Until now, there was no suitable criterion for determining the contamination level by using ATP meter in medical machines where sample area is small and reused. In this study, criteria for each category were set to measure the contamination level of ATP meter suitable for small sample area such as ultrasound probe, so that contamination level could be determined in real time at the site. Therefore, it is considered that hygiene management for ultrasound probe can be more actively performed.

• 한국산학기술학회논문지
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• 제3권2호
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• pp.74-79
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• 2002

80년대 반도체 산업의 급격한 성장으로 오늘날 반도체 산업은 반도체소자의 초고집접화, 웨이퍼의 대구경화로 발전이 거듭났으며, 소자의 성능과 생산 수율의 향상을 위하여 실리콘 웨이퍼의 세정하는 기술 및 연구를 계속 진행하고 있다. 기존의 반도체 세정은 과다한 화학약품의 사용으로 비 환경친화적이며, 이에 본 연구에서는 기존의 세정방법을 대체하기 위한 방법으로 환경친화적인 전리수를 이용한 반도체 세정법을 하였다. 이때 실리콘 웨이퍼 표면의 원자적 상태의 변화가 발생하여 다양한 방법으로 확인할 수 있다. 본 연구에 서는 이러한 분석을 하기 위하여 기존세정의 화학약품과 전리수로 세정한 웨이퍼의 표면을 비교하였으며, 또한 온도 및 시간별 표면상태변화를 분석하였다. 특히 접촉각 변하에 중점을 두어 변화를 관찰하였으며, 음극수의 경우 17.28°, 양극수의 경우 34.1°의 낮은 접촉각을 얻을 수 있었다.

• 한국진공학회지
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• 제9권2호
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• pp.102-109
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• 2000

chemical mechanical Polishing (CMP)공정 중 제거된 막과 연마재의 지꺼기를 제거하기 위하여 일반적으로 사용하는 scrubbing과 같은 기계적인 세정법으로는 기가급 소자 제조시에 요구되는 $10^{10}/\textrm{cm}^2$ 이하의 오염도에 도달하기 어렵다. 따라서 이러한 기계적인 세정법에 이어 충분히 제거되지 못한 금속오염물을 제거하기 위한 2차 세정이 요구된다. 본 논문에서는 리모트 플라스마 세정법과 UV/$O_3$ 세정법을 사용하여 oxide CMP 후에 웨이퍼 표면에 많이 존재하는 K, Fe, Cu등의 금속오염물을 제거하는데 대한 연구결과를 보고하고자 한다. 리모트 수소 플라스마 세정결과에 의하면, 세정시간이 짧을 수록, rf-power가 증가할수록 세정 효과가 우수한 것으로 나타났으며, CMP 공정 후 웨이퍼 표면에 특히 많이 존재하는 금속 불순물인 K, Fe, Cu 등의 오염 제거를 위한 최적 공정 조건은 세정시간이 1분, rf-power가 100 W인 것으로 나타났다. AFM 분석 결과에 의하면 rf-power의 증가에 따라 표면 거칠기가 미소하게 증가하는데 , 이것은 플라스마에 의한 손상 때문인 것으로 보이나 그 정도는 무시할만하다. 한편, UV/$O_3$ 세정의 경우에는 세정공정시간이 30 sec일때 가장 우수한 세정효과가 얻어졌다. 리모트 수소 플라스마 및 UV/$O_3$ 세정방법에 의한 Si 웨이퍼 표면의 금속 불순물 제거기구는 Si표면 금속오염의 하단층에 생성된 $SiO_2H^+$/ 및 $e^-$와 반응하여 $SiO^*$상태로 휘발될 때 금속불순물이 $SiO^*$에 묻어서 함께 제거되는 것으로 사료된다.

• 한국재료학회:학술대회논문집
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• 한국재료학회 2010년도 춘계학술발표대회
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• pp.24.1-24.1
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• 2010

In practical operation, the exposed surfaces may get dirty thus degrade the performance of devices. So the combination of self cleaning and antireflection is very desirable for use in outdoor photovoltaic and displaying devices, self cleaning windows and car windshields. For the purpose of self cleaning, the surface needs to be either superhydrophobic or superhydrophilic. However, in practice AR in the visible region and self cleaning are a pair of competitive properties. To satisfy the requirements for superhydrophobic or superhydrophilic surfaces, high surface roughness is required. But it usually cause severely light scattering. Photo-responsive coatings (TiO2, ZnO etc.) can lead to superhydrophilic. However, the refractive indices are high. Thus for porous structure, controlling pore size in the underwavelength scale to reduce the light scattering is very crucial for highly transparent and self cleaning antireflection coating. Herein, we demonstrate a simple method to make high performance broadband antireflection layer on the glass surface, by "carving" the surface by hot alkali solution. Etched glass has superhydrophilic surface. By chemical modification, it turns to superhydrophobic. Enhanced transparency (up to 97%) in a broad wavelength range was obtained by short time etching. Also antifogging effect has been demonstrated, which may offer advantage for devices working at high humidity environment or underwater. Compositional dependence of the properties was observed by comparing three different commercially available glasses.

• Transactions on Electrical and Electronic Materials
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• 제14권5호
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• pp.254-257
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• 2013

In-situ optical emission spectroscopy (OES) is employed for PECVD chamber monitoring. OES is used as an addon sensor to monitoring and cleaning end point detection (EPD). On monitoring plasma chemistry using OES, the process gas and by-product gas are simultaneously monitored. Principal component analysis (PCA) enhances the capability of end point detection using OES data. Through chamber cleaning monitoring using OES, cleaning time is reduced by 53%, in general. Therefore, the gas usage of fluorine is also reduced, so satisfying Green Fab challenge in semiconductor manufacturing.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2012년도 춘계학술발표대회 논문집
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• pp.248-254
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• 2012

In the situation of expanding domestic solar power supply business long-term performance modeling of a proposed solar-cooling and cleaning system to increase electromotive force and light transmission is carried out to test the effectiveness of the system. To test the effectiveness of the system, the data which comparing the solar power planet installing the system to not installing at the same time is used. A difference between the utilization factor of each comparison group were recorded. Approximately from one year to two years Field Test was performed, Result of apply to cooling/cleaning technology, Each of plant by From least 7 percent up to 16 percent utilization factor increased, and the cooling / cleaning is output through improved as a result of the determined.

• 한국레이저가공학회지
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• 제7권1호
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• pp.29-36
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• 2004

The dynamics of laser-induced plasma/shock wave and the interaction with a surface in the laser shock cleaning process are analyzed by optical diagnostics. Shock wave is generated by a Q-switched Nd:YAG laser in air or with N$_2$, Ar, and He injection into the focal spot. The shock speed is measured by monitoring the photoacoustic probe-beam deflection signal under different conditions. In addition, nanosecond time-resolved images of shock wave propagation and interaction with the substrate are obtained by the laser-flash shadowgraphy. The results reveal the effect of various operation parameters of the laser shock cleaning process on shock wave intensity, energy-conversion efficiency, and flow characteristics. Discussions are made on the cleaning mechanisms based on the experimental observations.

• KEPCO Journal on Electric Power and Energy
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• 제7권1호
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• pp.73-77
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• 2021

As the big data analysis technologies has been developed worldwide, the importance of asset management for electric power facilities based data analysis is increasing. It is essential to secure quality of data that will determine the performance of the RISK evaluation algorithm for asset management. To improve reliability of asset management, asset data must be preprocessed. In particular, the process of cleaning dirty data is required, and it is also urgent to develop an algorithm to reduce time and improve accuracy for data treatment. In this paper, the result of the development of an automatic cleaning algorithm specialized in overhead transmission asset data is presented. A data cleaning algorithm was developed to enable data clean by analyzing quality and overall pattern of raw data.

• Journal of Information Processing Systems
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• 제19권2호
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• pp.149-163
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• 2023

Affected by external factors, errors in time series data collected by sensors are common. Using the traditional method of constraining the speed change rate to clean the errors can get good performance. However, they are only limited to the data of stable changing speed because of fixed constraint rules. Actually, data with uneven changing speed is common in practice. To solve this problem, an online cleaning algorithm for time series data based on dynamic speed change rate constraints is proposed in this paper. Since time series data usually changes periodically, we use the extreme learning machine to learn the law of speed changes from past data and predict the speed ranges that change over time to detect the data. In order to realize online data repair, a dual-window mechanism is proposed to transform the global optimal into the local optimal, and the traditional minimum change principle and median theorem are applied in the selection of the repair strategy. Aiming at the problem that the repair method based on the minimum change principle cannot correct consecutive abnormal points, through quantitative analysis, it is believed that the repair strategy should be the boundary of the repair candidate set. The experimental results obtained on the dataset show that the method proposed in this paper can get a better repair effect.