• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.14-18
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• 2021

Electric Vehicle industry requires high technologies to stabilize apparatuses for the Coolant heater manufacturing. Vibrations of Leak Machine are one of the most critical factors for causing delivered of the defective product or poor inspection, which are the main reasons of the defects. In this study, the structure of the Leak Machine was analyzed through the experiment and the computer simulation to investigate the main reasons of the vibrations, and further to alter the design for the improved stability. And that design alterations were applied to the machine to identify the effects of those alterations. The result of the study shows that design alterations of the Leak Machine can effectively suppress about 97.8% of the vibrations, and further can improving the Inspection precision of the Coolant heater.

• Journal of the Semiconductor & Display Technology
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• v.5 no.2 s.15
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• pp.33-36
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• 2006

Many issues arose to use the Pb-free solder as adhesive materials in MEMS ICs and packaging. Then this study for easy and simple sealing method using adhesive materials was carried out to maintain hermetic characteristic in MEMS Package. In this study, Hermetic characteristic using negative PR (XP SU-8 3050 NO-2) as adhesive at the interface of Si test coupon/glass substrate and Si test coupon/LTCC substrate was examined. For experiment, the dispenser pressure was 4 MPa and the $200\;{\mu}m{\Phi}$ syringe nozzle was used. 3.0 mm/sec as speed of dispensing and 0.13 mm as the gap between Si test coupon and nozzle was selected to machine condition. 1 min at $65^{\circ}C$ and 15 min at $95^{\circ}C$ as Soft bake, $200\;mj/cm^2$ expose in 365 nm wavelength as UV expose, 1 min at $65^{\circ}C$ and 6 min at $95^{\circ}C$ as Post expose bake, 60 min at $150^{\circ}C$ as hard bake were selected to activation condition of negative PR. Hermetic sealing was achieved at the Si test coupon/ glass substrate and Si test coupon/LTCC substrate. The leak rate of Si test coupon/glass substrate was $5.9{\times}10^{-8}mbar-l/sec$, and there was no effect by adhesive method. The leak rate of Si test coupon/LTCC substrate was $4.9{\times}10^{-8}mbar-l/sec$, and there was no effect by dispensing cycle. Better leak rate value could be achieved to use modified substrate which prevent PR flow, to increase UV expose energy and to use system that controls gap automatically with vision.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.160-160
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• 2019

Water is a limited source that needs to be properly managed and distributed to the ever-growing population of the world. Rapid urbanization and development have increased the overall water demand of the world drastically. However, there is loss of billions of liters of water every year due to leakages in water distribution systems. Such water loss means significant financial loss for the utilities as well. World bank estimates a loss of $14 billion annually from wasted water. To address these issues and for the development of efficient and reliable leakage management techniques, high efforts have been made by the researchers and engineers. Over the past decade, various techniques and technologies have been developed for leakage management and leak detection. These include ideas such as pressure management in water distribution networks, use of Advanced Metering Infrastructure, use of machine learning algorithms, etc. For leakage detection, techniques such as acoustic technique, and in recent yeats transient test-based techniques have become popular. Smart Water Grid uses two-way real time network monitoring by utilizing sensors and devices in the water distribution system. Hence, valuable real time data of the water distribution network can be collected. Best results and outcomes may be produced by proper utilization of the collected data in unison with advanced detection and management techniques. Long term reduction in Non Revenue Water can be achieved by detecting, localizing and repairing leakages as quickly and as efficiently as possible. However, there are still numerous challenges to be met and future research works to be conducted in this field.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.33-41
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• 2022

In this article, we proposed to predict natural gas (NG) leakage levels through feature selection based on a factor analysis (FA) of the integrating the Korean Meteorological Agency data and natural gas leakage data for considering complex factors. The paper has been divided into three modules. First, we filled missing data based on the linear interpolation method on the integrated data set, and selected essential features using FA with OrdinalEncoder (OE)-based normalization. The dataset is labeled by K-means clustering. The final module uses four algorithms, K-nearest neighbors (KNN), decision tree (DT), random forest (RF), Naive Bayes (NB), to predict gas leakage levels. The proposed method is evaluated by the accuracy, area under the ROC curve (AUC), and mean standard error (MSE). The test results indicate that the OrdinalEncoder-Factor analysis (OE-F)-based classification method has improved successfully. Moreover, OE-F-based KNN (OE-F-KNN) showed the best performance by giving 95.20% accuracy, an AUC of 96.13%, and an MSE of 0.031.