• Journal of the Korean Society of Industry Convergence
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• v.26 no.2_1
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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.

• Journal of radiological science and technology
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• v.43 no.1
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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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.3 no.2
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• pp.74-79
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• 2002

In the a rapid changes of the semiconductor manufacturing technologies for early 21st century, it may be safely said that a kernel of terms is the size increase of Si wafer and the size decrease of semiconductor devices. As the size of Si wafers increases and semiconductor device is miniaturized, the units of cleaning processes increases. A present cleaning technology is based upon RCA cleaning which consumes vast chemicals and ultra pure water (UPW) and is the high temperature process. Therefore, this technology gives rise to the environmental issue. To resolve this matter, candidates of advanced cleaning processes has been studied. One of them is to apply the electrolyzed water. In this work, Compared with surface on Si wafer with electrolyzed water cleaning and various chemicals cleaning, and analyzed Si wafer surface condition treated with elecoolyzed water by cleaning temperature and cleaning time. Especially. concentrate upon the contact angle. finally, contact angle on surface treated with cathode water cleaning is 17.28, and anode water cleaning is 34.1.

• Journal of the Korean Vacuum Society
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• v.9 no.2
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• pp.102-109
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• 2000

It is difficult to meet the cleanliness requirement of $10^{10}/\textrm{cm}^2$ for the giga level device fabrication with mechanical cleaning techniques like scrubbing which is widely used to remove the particles generated during Chemical Mechanical Polishing (CMP) processes. Therefore, the second cleaning process is needed to remove metallic contaminants which were not completely removed during the mechanical cleaning process. In this paper the experimental results for the removal of the metallic contaminants existing on the wafer surface using remote plasma $H_2$ cleaning and UV/$O_3$ cleaning techniques are reported. In the remote plasma $H_2$ cleaning the efficiency of contaminants removal increases with decreasing the plasma exposure time and increasing the rf-power. Also the optimum process conditions for the removal of K, Fe and Cu impurities which are easily found on the wafer surface after CMP processes are the plasma exposure time of 1min and the rf-power of 100 W. The surface roughness decreased by 30-50 % after remote plasma $H_2$ cleaning. On the other hand, the highest efficiency of K, Fe and Cu impurities removal was achieved for the UV exposure time of 30 sec. The removal mechanism of the metallic contaminants like K, Fe and Cu in the remote plasma $H_2$ and the UV/$O_3$ cleaning processes is as follows: the metal atoms are lifted off by $SiO^*$ when the $SiO^*$is evaporated after the chemical $SiO_2$ formed under the metal atoms reacts with $H^+ \; and\; e^-$ to form $SiO^*$.

• Proceedings of the Materials Research Society of Korea Conference
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• 2010.05a
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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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• v.14 no.5
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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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• 2012.03a
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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.

• Laser Solutions
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• v.7 no.1
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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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• v.7 no.1
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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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• v.19 no.2
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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.