• Journal of the Korean Vacuum Society
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• v.17 no.1
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• pp.16-22
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• 2008

We studied plasma etching of polycarbonate in $O_2/SF_6$, $O_2/N_2$ and $O_2/CH_4$. A capacitively coupled plasma system was employed for the research. For patterning, we used a photolithography method with UV exposure after coating a photoresist on the polycarbonate. Main variables in the experiment were the mixing ratio of $O_2$ and other gases, and RF chuck power. Especially, we used only a mechanical pump for in order to operate the system. The chamber pressure was fixed at 100 mTorr. All of surface profilometry, atomic force microscopy and scanning electron microscopy were used for characterization of the etched polycarbonate samples. According to the results, $O_2/SF_6$ plasmas gave the higher etch rate of the polycarbonate than pure $O_2$ and $SF_6$ plasmas. For example, with maintaining 100W RF chuck power and 100 mTorr chamber pressure, 20 sccm $O_2$ plasma provided about $0.4{\mu}m$/min of polycarbonate etch rate and 20 sccm $SF_6$ produced only $0.2{\mu}m$/min. However, the mixed plasma of 60 % $O_2$ and 40 % $SF_6$ gas flow rate generated about $0.56{\mu}m$ with even low -DC bias induced compared to that of $O_2$. More addition of $SF_6$ to the mixture reduced etch of polycarbonate. The surface roughness of etched polycarbonate was roughed about 3 times worse measured by atomic force microscopy. However examination with scanning electron microscopy indicated that the surface was comparable to that of photoresist. Increase of RF chuck power raised -DC bias on the chuck and etch rate of polycarbonate almost linearly. The etch selectivity of polycarbonate to photoresist was about 1:1. The meaning of these results was that the simple capacitively coupled plasma system can be used to make a microstructure on polymer with $O_2/SF_6$ plasmas. This result can be applied to plasma processing of other polymers.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.54 no.4
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• pp.390-396
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• 2009

To select optimal shade material in paddy soil, growth characteristics and ginsenoside contents were investigated in new cultivar, 'Cheonpoong' of three-year-old ginseng cultured under three kinds of shade materials such as three-layered blue and one-layered black PE (polyethylene) net (TBPN), blue PE sheet (BPSS), and aluminium-coated PE sheet (APSS). The order of light transmission ratio and air temperature by shade materials were BPSS > APSS > TBSB among three shade materials. Average soil water tension in PDC and IDC was 64 mbar (absolute soil moisture, 25%) and 123 mbar (absolute soil moisture, 17%), respectively, and soil water tension in IDC was changed more distinctly than that of PDC by season and shade materials. Yield in PDC was distinctly decreased more than that in IDC because of the increase of discolored-leaf and rusted-root ratio. BPSS and TBPN among three shade materials were the most effective on the increase of yield in PDC and IDC, respectively. Ratio of rusty-colored root showed not significant difference by drainage class and shade materials. Contents of panaxatriol ginsenoside (Rg1, Re and Rf) were decreased in PDC, while it of panaxadiol ginsenoside (Rb1, Rc and Rd) were increased in IDC. Total ginsenoside contents of IDC was distinctly higher than that of PDC, and BPSS showed the highest contents among three shade materials regardless of poorly and imperfectly drainage class.

• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.31-44
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• 2009

The objective of this study was to measure backscattering coefficients of paddy rice using a L-, C-, and X-band scatterometer system with full polarization and various angles during the rice growth period and to relate backscattering coefficients to rice growth parameters. Radar backscattering measurements of paddy rice field using multifrequency (L, C, and X) and full polarization were conducted at an experimental field located in National Academy of Agricultural Science (NAAS), Suwon, Korea. The scatterometer system consists of dual-polarimetric square horn antennas, HP8720D vector network analyzer ($20\;MHz{\sim}20\;GHz$), RF cables, and a personal computer that controls frequency, polarization and data storage. The backscattering coefficients were calculated by applying radar equation for the measured at incidence angles between $20^{\circ}$ and $60^{\circ}$ with $5^{\circ}$ interval for four polarization (HH, VV, HV, VH), respectively. We measured the temporal variations of backscattering coefficients of the rice crop at L-, C-, X-band during a rice growth period. In three bands, VV-polarized backscattering coefficients were higher than hh-polarized backscattering coefficients during rooting stage (mid-June) and HH-polarized backscattering coefficients were higher than VV-, HV/VH-polarized backscattering coefficients after panicle initiation stage (mid-July). Cross polarized backscattering coefficients in X-band increased towards the heading stage (mid-Aug) and thereafter saturated, again increased near the harvesting season. Backscattering coefficients of range at X-band were lower than that of L-, C-band. HH-, VV-polarized ${\sigma}^{\circ}$ steadily increased toward panicle initiation stage and thereafter decreased, and again increased near the harvesting season. We plotted the relationship between backscattering coefficients with L-, C-, X-band and rice growth parameters. Biomass was correlated with L-band hh-polarization at a large incident angle. LAI (Leaf Area Index) was highly correlated with C-band HH- and cross-polarizations. Grain weight was correlated with backscattering coefficients of X-band VV-polarization at a large incidence angle. X-band was sensitive to grain maturity during the post heading stage.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1031-1042
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• 2023

In this study, a deep learning model was developed to predict the yield of cabbage and radish, one of the five major supply and demand management vegetables, using satellite images of Landsat 8. To predict the yield of cabbage and radish in Gangwon-do from 2015 to 2020, satellite images from June to September, the growing period of cabbage and radish, were used. Normalized difference vegetation index, enhanced vegetation index, lead area index, and land surface temperature were employed in this study as input data for the yield model. Crop yields can be effectively predicted using satellite images because satellites collect continuous spatiotemporal data on the global environment. Based on the model developed previous study, a model designed for input data was proposed in this study. Using time series satellite images, convolutional neural network, a deep learning model, was used to predict crop yield. Landsat 8 provides images every 16 days, but it is difficult to acquire images especially in summer due to the influence of weather such as clouds. As a result, yield prediction was conducted by splitting June to July into one part and August to September into two. Yield prediction was performed using a machine learning approach and reference models , and modeling performance was compared. The model's performance and early predictability were assessed using year-by-year cross-validation and early prediction. The findings of this study could be applied as basic studies to predict the yield of field crops in Korea.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.35-44
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• 2024

Research in dam inflow prediction has actively explored the utilization of data-driven machine learning and deep learning (ML&DL) tools across diverse domains. Enhancing not just the inherent model performance but also accounting for model characteristics and preprocessing data are crucial elements for precise dam inflow prediction. Particularly, existing rainfall data, derived from snowfall amounts through heating facilities, introduces distortions in the correlation between snow accumulation and rainfall, especially in dam basins influenced by snow accumulation, such as Soyang Dam. This study focuses on the preprocessing of rainfall data essential for the application of ML&DL models in predicting dam inflow in basins affected by snow accumulation. This is vital to address phenomena like reduced outflow during winter due to low snowfall and increased outflow during spring despite minimal or no rain, both of which are physical occurrences. Three machine learning models (SVM, RF, LGBM) and two deep learning models (LSTM, TCN) were built by combining rainfall and inflow series. With optimal hyperparameter tuning, the appropriate model was selected, resulting in a high level of predictive performance with NSE ranging from 0.842 to 0.894. Moreover, to generate rainfall correction data considering snow accumulation, a simulated snow accumulation algorithm was developed. Applying this correction to machine learning and deep learning models yielded NSE values ranging from 0.841 to 0.896, indicating a similarly high level of predictive performance compared to the pre-snow accumulation application. Notably, during the snow accumulation period, adjusting rainfall during the training phase was observed to lead to a more accurate simulation of observed inflow when predicted. This underscores the importance of thoughtful data preprocessing, taking into account physical factors such as snowfall and snowmelt, in constructing data models.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.3
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• pp.219-232
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• 2013

This paper presents a microstrip antenna which recovers its resonant frequency and impedance shifted automatically by the approach of other objects such as hands. This can be used for telemetry sensor applications in the ultrahigh frequency(UHF) industrial, scientific, and medical(ISM) band. It is the key element that an frequency-reconfigurable antenna could be electrically controlled. This antenna is miniaturized by loading the folded plates at both radiating edges, and varactor diodes are installed between the radiating edges and the ground plane to control the resonant frequency by adjusting the DC bias asymmetrically. Using this voltage-controlled antenna and the micro controller peripheral circuits of reading the returned level, the antenna is designed and fabricated which recovers its resonant frequency and impedance automatically. Designed frequency auto recovering antenna is conformed to be recovered within a few seconds when the resonant frequency and impedance are shifted by the approach of other objects such as hand, metal plate, dielectric and so on.

• Korean Journal of Materials Research
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• v.22 no.4
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• pp.180-184
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• 2012

Nanostructures of ZnO, such as nanowires, nanorods, nanorings, and nanobelts have been actively studied and applied in electronic or optical devices owing to the increased surface to volume ratio and quantum confinement that they provide. ZnO seed layer (about 40 nm thick) was deposited on Si(100) substrate by RF magnetron sputtering with power of 60 W for 5 min. ZnO nanorods were grown on ZnO seed layer/Si(100) substrate at $95^{\circ}C$ for 5 hr by hydrothermal method with concentrations of $Zn(NO_3)_2{\cdot}6H_2O$ [ZNH] and $(CH_2)_6N_4$ [HMT] precursors ranging from 0.02M to 0.1M. We observed the microstructure, crystal structure, and photoluminescence of the nanorods. The ZnO nanorods grew with hexahedron shape to the c-axis at (002), and increased their diameter and length with the increase of precursor concentration. In 0.06 M and 0.08 M precursors, the mean aspect ratio values of ZnO nanorods were 6.8 and 6.5; also, ZnO nanorods had good crystal quality. Near band edge emission (NBE) and a deep level emission (DLE) were observed in all ZnO nanorod samples. The highest peak of NBE and the lower DLE appeared in 0.06 M precursor; however, the highest peak of DLE and the lower peak of NBE appeared in the 0.02 M precursor. It is possible to explain these phenomena as results of the better crystal quality and homogeneous shape of the nanorods in the precursor solution of 0.06 M, and as resulting from the bed crystal quality and the formation of Zn vacancies in the nanorods due to the lack of $Zn^{++}$ in the 0.02 M precursor.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.80-80
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• 2010

유리기판위에 큰 결정입자를 갖는 실리콘 (폴리 실리콘) 박막을 제조하는 것은 가격저가화 및 대면적화 측면 같은 산업화의 높은 잠재성을 가지고 있기 때문에 그동안 많은 관심을 가지고 연구되어 오고 있다. 다양한 방법을 이용하여 다결정 실리콘 박막을 만들기 위해 노력해 오고 있으며, 태양전지에 응용하기 위하여 연속적이면서 10um이상의 큰 입자를 갖는 다결정 실리콘 씨앗층이 필요하며, 고속증착을 위해서는 (100)의 결정성장방향 등 다양한 조건이 제시될 수 있다. 다결정 실리콘 흡수층의 품질은 고품질의 다결정 실리콘 씨앗층에서 얻어질 수 있다. 이러한 다결정 실리콘의 에피막 성장을 위해서는 유리기판의 연화점이 저압 화학기상증착법 및 아크 플라즈마 등과 같은 고온기반의 공정 적용의 어려움이 있기 때문에 제약 사항으로 항상 문제가 제기되고 있다. 이러한 관점에서 볼때 유리기판위에 에피막을 성장시키는 방법으로 많지 않은 방법들이 사용될 수 있는데 전자 공명 화학기상증착법(ECR-CVD), 이온빔 증착법(IBAD), 레이저 결정화법(LC) 및 펄스 자석 스퍼터링법 등이 에피 실리콘 성장을 위해 제안되는 대표적인 방법으로 볼 수 있다. 이중에서 효율적인 관점에서 볼때 IBAD는 산업화측면에서 좀더 많은 이점을 가지고 있으나, 박막을 형성하는 과정에서 큰 에너지 및 이온크기의 빔 사이즈 등으로 인한 표면으로의 damages가 일어날 수 있어 쉽지 않는 방법이 될 수 있다. 여기에서는 이러한 damage를 획기적으로 줄이면서 저온에서 결정화 시킬 수 있는 cold annealing법을 소개하고자 한다. 이온빔에 비해서 전자빔의 에너지와 크기는 그리드 형태의 렌즈를 통해 전체면적에 조사하는 것을 쉽게 제어할 수 있으며 이러한 전자빔의 생성은 금속 필라멘트의 열전자가 아닌 Ar플라즈마에서 전자의 분리를 통해 발생된다. 유리기판위에 다결정 실리콘 씨앗층을 제조하기 위하여 전자빔을 조사하는 방법과 Al을 이용한 씨앗층 제조법이 비교되어 공정 수행이 이루어진다. 우선, 전자빔 조사를 위해 DC 및 RF 스퍼터링법을 이용하여 ${\sim}10^{20}cm^{-3}$이상의 농도를 갖는 $p^+^+$ 비정질 실리콘 박막을 제조한다. Al의 증착은 DC 스퍼터링법을 이용하여 제조하고 그 두께는 실리콘 박막의 두께와 동일한 조건(350nm)으로 제조한다. 제조된 샘플은 E-beam gun이 달린 챔버로 이동하여 1.4keV의 세기를 가지고 각각 10, 20, 50, 100초를 조사한 후 단면의 이미지를 SEM으로, 결정화 정도를 Raman으로, 결정화 방향 등에 대한 조사를 XRD로 분석 측정한다. 그리고 Hall effect를 통해 전자빔의 조사 전후의 캐리어 농도, 이동도 및 비저항 등에 대한 조사가 이루어진다. 동시에 Al을 촉매로 한 layer교환에 대하여 마찬가지로 분석을 통하여 최종적으로 비교분석이 이루어 진다. 전자빔을 조사한 샘플에 대하여 빠른 시간 및 캐리어농도 제어 등의 우수성이 보이며, 특히 ~98%이상의 결정화율을 보일 것으로 예상된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.7
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• pp.4689-4696
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• 2015

The purpose of this study was to evaluate biomechanical characteristics of trekking shoes using 3D Bootie method as mimics barefoot form of F Co. that provides the best comfort and plantar pressure dispersion. The control group is normal trekking shoes of M Co. and K Co.. 13 healthy males measured the foot pressure, EMG and GRF. Collected data was analyzed using One-way ANOVA in order to investigate the effects of each trekking shoes. The results are as follows: Trekking shoe of F Co. was significantly wider in contact area than others at MF and significantly lower in maximum force, peak pressure than others at RF. In the case of muscle activity, acted in the same way as the effect of barefoot walking. In the case of GRF, effectively absorbed the impact force, so it is possible to efficient walking. As a result of the analysis, trekking shoe using of 3D Bootie method of F Co. can be efficient walking by reducing the load of foot during walking.