• Proceedings of the Korea Concrete Institute Conference
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• 2008.11a
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• pp.785-788
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• 2008

This study is focused on applying heavyweight concrete to ballast used to have stability of a ship. Generally, heavyweight concrete is made from a high density aggregate like magnetite or limonite. However, these materials are hard to obtain them from relevant companies and so expensive. Therefore, this study plans to product heavyweight ballast concrete which is easy to obtain by recycled iron slag. Heavyweight ballast concrete isn't required to meet some compressive strength in use, but it is required to have high flowable and 2.7t/m3 of bulk density to fill the ballast tank densely. The designed field mix proportion of concrete based on the results of pre-experiment shows it can control the temperature crack and has superior chloride corrosion resistance after conducting chloride corrosion experiment. Also, it is prefer that before airtightness voltile corrosion inhibiter(VCI) is added in airtight space of shipyard.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.10
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• pp.403-410
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• 2019

Image de-snowing aims at eliminating the negative influence by snow particles and improving scene understanding in images. In this paper, a perceptual generative adversarial network based a single image snow removal method is proposed. The residual U-Net is designed as a generator to generate the snow free image. In order to handle various sizes of snow particles, the inception module with different filter kernels is adopted to extract multiple resolution features of the input snow image. Except the adversarial loss, the perceptual loss and total variation loss are employed to improve the quality of the resulted image. Experimental results indicate that our method can obtain excellent performance both on synthetic and realistic snow images in terms of visual observation and commonly used visual quality indices.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.1-12
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• 2021

An objective expert discrimination scheme is needed for finding researchers who have insight and knowledge about a particular field of research. There are two types of expert discrimination schemes such as a citation graph based method and a formula based method. In this paper, we propose an efficient expert discrimination scheme considering various characteristics that have not been considered in the existing formula based methods. In order to discriminate the expertise of researchers, we present six expertise indices such as quality, productivity, contributiveness, recentness, accuracy, and durability. We also consider the number of social citations to apply the characteristics of academic search sites. Finally, we conduct various experiments to prove the validity and feasibility of the proposed scheme.

• Composites Research
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• v.37 no.2
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• pp.68-75
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• 2024

Polypropylene (PP), a thermoplastic resin with excellent mechanical, thermal, chemical, and water resistance properties, has been attracting attention due to its economic efficiency and recyclability. However, repeated processing of thermoplastic resins can lead to property degradation, and the point at which quality degradation occurs varies depending on the processing conditions. In this study, we evaluated the performance changes of composite materials with repeated processing by blending PP resin with various additives and conducting extrusion and injection processes repeatedly. In addition, we evaluated the mechanical properties of composite materials to evaluate the effect of MFI value change during repeated processing on fiber impregnation in composite material processing.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.441-448
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• 2015

Lack of agricultural information for food supply and demand in Democratic People's republic Korea(DPRK) make people sometimes confused for right and timely decision for policy support. We carried out a study to estimate paddy rice yield in DPRK using MODIS NDVI reflecting rice growth and climate data. Mean of MODIS $NDVI_{max}$ in paddy rice over the country acquired and processed from 2002 to 2014 and accumulated rainfall collected from 27 weather stations in September from 2002 to 2014 were used to estimated paddy rice yield in DPRK. Coefficient of determination of the multiple regression model was 0.44 and Root Mean Square Error(RMSE) was 0.27 ton/ha. Two-way analysis of variance resulted in 3.0983 of F ratio and 0.1008 of p value. Estimated milled rice yield showed the lowest value as 2.71 ton/ha in 2007, which was consistent with RDA rice yield statistics and the highest value as 3.54 ton/ha in 2006, which was not consistent with the statistics. Scatter plot of estimated rice yield and the rice yield statistics implied that estimated rice yield was higher when the rice yield statistics was less than 3.3 ton/ha and lower when the rice yield statistics was greater than 3.3 ton/ha. Limitation of rice yield model was due to lower quality of climate and statistics data, possible cloud contamination of time-series NDVI data, and crop mask for rice paddy, and coarse spatial resolution of MODIS satellite data. Selection of representative areas for paddy rice consisting of homogeneous pixels and utilization of satellite-based weather information can improve the input parameters for rice yield model in DPRK in the future.

• Journal of the Korean Applied Science and Technology
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• v.34 no.4
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• pp.874-882
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• 2017

As the interest on the air-pollution is gradually rising up at home and abroad, automotiv e and fuel researchers have been working on the exhaust emission reduction from vehicles through a lot of approaches, which consist of new engine design, innovative after-treatment systems, using clean (eco-friendly alternative) fuels and fuel quality improvement. This research has brought forward three main issues : evaporative, performance, air pollution. In addition, researcher studied the environment problems of the bio-ethanol, bio-butanol, bio-ETBE (Ethyl Tertiary Butyl Ether), MTBE (Methyl Tert iary Butyl Ether) fuel contained in the fuel as octane number improver. The researchers have many dat a about the health effects of ingestion of octane number improver. However, the data support the con clusion that octane number improver is a potential human carcinogen at high doses. Based on the bio-fuel and octane number improver types (bio-ethanol, bio-butanol, bio-ETBE, MTBE), this paper dis cussed the influence of gasoline fuel properties on the evaporative emission characteristics. Also, this p aper assessed the acceleration and power performance of gasoline vehicle for the bio-fuel property. As a result of the experiment, it was found that all the test fuels meet the domestic exhaust gas standards, and as a result of measurement of the vapor pressure of the test fuels, the bio - ethanol : 15 kPa and the biobutanol : 1.6 kPa. thus when manufacturing E3 fuel, Increasing the biobutanol content reduces evaporation gas and vapor pressure. In addition, Similar accelerating and powering performance was shown for the type of biofuel and when bio-butanol and bio-ethanol were compared accelerated perf ormance was improved by about 3.9% and vehicle power by 0.8%.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.88-88
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• 2017

감자 재배 기계화를 위한 전자동 감자 파종기의 기구적인 개념 설계를 수행하고, 시작기를 제작하였다. 시작기의 성능평가를 통해 기계화에 적합한 감자 재배양식에 대한 연구 필요성이 대두되었다. 본 연구의 목적은 감자 재배 양식에 따른 주요 감자의 생육 사항, 수량성, 상품성 및 품질, 주요 생리 장애등을 측정하여 기계파종 후 재배상의 문제점 파악과 파종 시 기계적인 미비점을 파악하여 개선방안을 마련하는데 있다. 기존의 국내 관행적 감자 재배 작형별 재배방식은 1줄 재배의 경우 재배 형식이 둥근두둑 방식이며, 2줄 재배의 경우 평두둑 방식을 채택하고 있다. 감자 파종기를 이용한 기계화 재배의 경우 평두둑으로 2줄 재배 방법을 채택하였다. 본 연구는 공시품종인 수미를 이용하여 봄 재배 형식으로 강릉 재배단지에서 실시하였다. 감자 파종은 2016년 3월 31일에 실시하였으며, 재배기간 92일을 소요하여 수확은 2016년 6월 30일에 하였다. 기계파종의 경우 두둑형식은 평두둑 2줄 재배양식 흑색비닐(파종구 세절) 파종 방법으로 전자동 기계파종을 실시하였고, 인력 파종의 경우 기계 파종과 동일한 방식으로 인력으로 실시하였다. 기존의 재래적 방식인 관행파종은 두둑형식은 외줄 1줄 흑색비닐(유공) 파종 방법으로 인력파종을 실시하였다. 관행 파종 방법은 이랑사이 75-80cm, 주간거리 20-25cm, 흙덮기 8-12cm로 재식밀도는 5,000-5,300주/10a로 씨감자 160kg/10a 소요하여 파종하였다. 실험 결과 감자 파종방법별 출현율은 기계파종의 경우 79.9-88.4%, 인력파종의 경우 97.9-99.2%로 기계파종에서 인력파종대비 결주율이 10.0-18.5% 정도 발생되었다. 씨감자의 절단 방법은 4절에 비하여 2절에서 양호하였다. 상품 지수의 경우 관행파종을 기준(100)으로 기계 파종(90)과 인력 파종(103)은 4절로 작업한 곳에서 상품성이 높았다. 파종 전 싹틔우기 여부에 따라서는 생육 초기(30일 이전)에는 싹틔운 파종 방법이 양호하였으나, 생육 후기(30일 이후)에는 싹을 틔우지 않은 파종 방법이 양호하였다. 기계 파종을 이용한 4절 씨감자 파종은 부패율이 12.2%로 다른 대비군에 비해 높았다(1.9-7.6%). 수확량(kg/10a)은 기계파종에서 2,748-3,503 kg 으로 관행 3,883 kg 대비 71-90% 수준으로 나타났다. 싹틔우지 않은 감자 4절을 이용한 기계 파종 시 결주율이 18.5%, 부패율 12.2%으로 싹틔운 감자 2절을 이용한 기계 파종으로 할 경우 결주율 10%, 부패율 4.1% 으로 낮출 수 있다.

• Journal of the Korean Ceramic Society
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• v.38 no.11
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• pp.980-986
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• 2001

Bragg reflector type FBAR was fabricated on the Si(100) substrate. We measured a frequency response of the resonator at 5.2 GHz and analyzed it by numerical calculation considering actual acoustic losses of each layer in the structure. We fabricated nine layer Bragg reflector of W-SiO$_2$pairs using r.f. sputtering method and fabricated AlN piezoelectric and Al electrodes using pulsed dc sputtering. The return loss(S$_{11}$) of the fabricated Bragg reflector type FBAR was 12 dB at 5.38 GHz and the series resonance frequency(f$_{s}$) was 5.376 GHz and the parallel resonance frequency(f$_{p}$) was 5.3865 GHz. Effective electro-mechanical coupling constant (K$_{eff{^2}}$) and Quality factors(Q$_{s}$), the Figures of Merit of the resonator, were about 0.48% and 411, respectively. We extracted acoustic parameters of AlN piezoelectric and reflection coefficient of the Bragg reflector by numerical calculation. We could know that material acoustic impedance and wave velocity of AlN piezoelectric decreased for intrinsic value and the electromechanical coupling constant(K$_2$) value was very low owing to the poor quality of the AlN piezoelectric. Reflection coefficient of Bragg reflector was 0.99966 and reflection band was very wide from 2.5 to 9.5 GHz.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.384-392
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• 2022

The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R²: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.