• Title/Summary/Keyword: Life Prediction

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Improving Usage of the Korea Meteorological Administration's Digital Forecasts in Agriculture: 2. Refining the Distribution of Precipitation Amount (기상청 동네예보의 영농활용도 증진을 위한 방안: 2. 강수량 분포 상세화)

  • Kim, Dae-Jun;Yun, Jin I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.15 no.3
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    • pp.171-177
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    • 2013
  • The purpose of this study is to find a scheme to scale down the KMA (Korea Meteorological Administration) digital precipitation maps to the grid cell resolution comparable to the rural landscape scale in Korea. As a result, we suggest two steps procedure called RATER (Radar Assisted Topography and Elevation Revision) based on both radar echo data and a mountain precipitation model. In this scheme, the radar reflection intensity at the constant altitude of 1.5 km is applied first to the KMA local analysis and prediction system (KLAPS) 5 km grid cell to obtain 1 km resolution. For the second step the elevation and topography effect on the basis of 270 m digital elevation model (DEM) which represented by the Parameter-elevation Regressions on Independent Slopes Model (PRISM) is applied to the 1 km resolution data to produce the 270 m precipitation map. An experimental watershed with about $50km^2$ catchment area was selected for evaluating this scheme and automated rain gauges were deployed to 13 locations with the various elevations and slope aspects. 19 cases with 1 mm or more precipitation per day were collected from January to May in 2013 and the corresponding KLAPS daily precipitation data were treated with the second step procedure. For the first step, the 24-hour integrated radar echo data were applied to the KLAPS daily precipitation to produce the 1 km resolution data across the watershed. Estimated precipitation at each 1 km grid cell was then regarded as the real world precipitation observed at the center location of the grid cell in order to derive the elevation regressions in the PRISM step. We produced the digital precipitation maps for all the 19 cases by using RATER and extracted the grid cell values corresponding to 13 points from the maps to compare with the observed data. For the cases of 10 mm or more observed precipitation, significant improvement was found in the estimated precipitation at all 13 sites with RATER, compared with the untreated KLAPS 5 km data. Especially, reduction in RMSE was 35% on 30 mm or more observed precipitation.

Predicting Regional Soybean Yield using Crop Growth Simulation Model (작물 생육 모델을 이용한 지역단위 콩 수량 예측)

  • Ban, Ho-Young;Choi, Doug-Hwan;Ahn, Joong-Bae;Lee, Byun-Woo
    • Korean Journal of Remote Sensing
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    • v.33 no.5_2
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    • pp.699-708
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    • 2017
  • The present study was to develop an approach for predicting soybean yield using a crop growth simulation model at the regional level where the detailed and site-specific information on cultivation management practices is not easily accessible for model input. CROPGRO-Soybean model included in Decision Support System for Agrotechnology Transfer (DSSAT) was employed for this study, and Illinois which is a major soybean production region of USA was selected as a study region. As a first step to predict soybean yield of Illinois using CROPGRO-Soybean model, genetic coefficients representative for each soybean maturity group (MG I~VI) were estimated through sowing date experiments using domestic and foreign cultivars with diverse maturity in Seoul National University Farm ($37.27^{\circ}N$, $126.99^{\circ}E$) for two years. The model using the representative genetic coefficients simulated the developmental stages of cultivars within each maturity group fairly well. Soybean yields for the grids of $10km{\times}10km$ in Illinois state were simulated from 2,000 to 2,011 with weather data under 18 simulation conditions including the combinations of three maturity groups, three seeding dates and two irrigation regimes. Planting dates and maturity groups were assigned differently to the three sub-regions divided longitudinally. The yearly state yields that were estimated by averaging all the grid yields simulated under non-irrigated and fully-Irrigated conditions showed a big difference from the statistical yields and did not explain the annual trend of yield increase due to the improved cultivation technologies. Using the grain yield data of 9 agricultural districts in Illinois observed and estimated from the simulated grid yield under 18 simulation conditions, a multiple regression model was constructed to estimate soybean yield at agricultural district level. In this model a year variable was also added to reflect the yearly yield trend. This model explained the yearly and district yield variation fairly well with a determination coefficients of $R^2=0.61$ (n = 108). Yearly state yields which were calculated by weighting the model-estimated yearly average agricultural district yield by the cultivation area of each agricultural district showed very close correspondence ($R^2=0.80$) to the yearly statistical state yields. Furthermore, the model predicted state yield fairly well in 2012 in which data were not used for the model construction and severe yield reduction was recorded due to drought.

Development of a Window Program for Searching CpG Island (CpG Island 검색용 윈도우 프로그램 개발)

  • Kim, Ki-Bong
    • Journal of Life Science
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    • v.18 no.8
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    • pp.1132-1139
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    • 2008
  • A CpG island is a short stretch of DNA in which the frequency of the CG dinucleotide is higher than other regions. CpG islands are present in the promoters and exonic regions of approximately $30{\sim}60$% of mammalian genes so they are useful markers for genes in organisms containing 5-methylcytosine in their genomes. Recent evidence supports the notion that the hypermethylation of CpG island, by silencing tumor suppressor genes, plays a major causal role in cancer, which has been described in almost every tumor types. In this respect, CpG island search by computational methods is very helpful for cancer research and computational promoter and gene predictions. I therefore developed a window program (called CpGi) on the basis of CpG island criteria defined by D. Takai and P. A. Jones. The program 'CpGi' was implemented in Visual C++ 6.0 and can determine the locations of CpG islands using diverse parameters (%GC, Obs (CpG)/Exp (CpG), window size, step size, gap value, # of CpG, length) specified by user. The analysis result of CpGi provides a graphical map of CpG islands and G+C% plot, where more detailed information on CpG island can be obtained through pop-up window. Two human contigs, i.e. AP00524 (from chromosome 22) and NT_029490.3 (from chromosome 21), were used to compare the performance of CpGi and two other public programs for the accuracy of search results. The two other programs used in the performance comparison are Emboss-CpGPlot and CpG Island Searcher that are web-based public CpG island search programs. The comparison result showed that CpGi is on a level with or outperforms Emboss-CpGPlot and CpG Island Searcher. Having a simple and easy-to-use user interface, CpGi would be a very useful tool for genome analysis and CpG island research. To obtain a copy of CpGi for academic use only, contact corresponding author.

The Brassica rapa Tissue-specific EST Database (배추의 조직 특이적 발현유전자 데이터베이스)

  • Yu, Hee-Ju;Park, Sin-Gi;Oh, Mi-Jin;Hwang, Hyun-Ju;Kim, Nam-Shin;Chung, Hee;Sohn, Seong-Han;Park, Beom-Seok;Mun, Jeong-Hwan
    • Horticultural Science & Technology
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    • v.29 no.6
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    • pp.633-640
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    • 2011
  • Brassica rapa is an A genome model species for Brassica crop genetics, genomics, and breeding. With the completion of sequencing the B. rapa genome, functional analysis of the genome is forthcoming issue. The expressed sequence tags are fundamental resources supporting annotation and functional analysis of the genome including identification of tissue-specific genes and promoters. As of July 2011, 147,217 ESTs from 39 cDNA libraries of B. rapa are reported in the public database. However, little information can be retrieved from the sequences due to lack of organized databases. To leverage the sequence information and to maximize the use of publicly-available EST collections, the Brassica rapa tissue-specific EST database (BrTED) is developed. BrTED includes sequence information of 23,962 unigenes assembled by StackPack program. The unigene set is used as a query unit for various analyses such as BLAST against TAIR gene model, functional annotation using MIPS and UniProt, gene ontology analysis, and prediction of tissue-specific unigene sets based on statistics test. The database is composed of two main units, EST sequence processing and information retrieving unit and tissue-specific expression profile analysis unit. Information and data in both units are tightly inter-connected to each other using a web based browsing system. RT-PCR evaluation of 29 selected unigene sets successfully amplified amplicons from the target tissues of B. rapa. BrTED provided here allows the user to identify and analyze the expression of genes of interest and aid efforts to interpret the B. rapa genome through functional genomics. In addition, it can be used as a public resource in providing reference information to study the genus Brassica and other closely related crop crucifer plants.

The Simulation of Pore Size Distribution from Unsaturated Hydraulic Conductivity Data Using the Hydraulic Functions (토양 수리학적 함수를 이용한 불포화 수리전도도로부터 공극크기분포의 모사)

  • Yoon, Young-Man;Kim, Jeong-Gyu;Shin, Kook-Sik
    • Korean Journal of Soil Science and Fertilizer
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    • v.43 no.4
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    • pp.407-414
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    • 2010
  • Until now, the pore size distribution, PSD, of soil profile has been calculated from soil moisture characteristic data by water release method or mercury porosimetry using the capillary rise equation. But the current methods are often difficult to use and time consuming. Thus, in this work, theoretical framework for an easy and fast technique was suggested to estimate the PSD from unsaturated hydraulic conductivity data in an undisturbed field soil profile. In this study, unsaturated hydraulic conductivity data were collected and simulated by the variation of soil parameters in the given boundary conditions (Brooks and Corey soil parameters, ${\alpha}_{BC}=1-5L^{-1}$, b = 1 - 10; van Genuchten soil parameters, ${\alpha}_{VG}=0.001-1.0L^{-1}$, m = 0.1 - 0.9). Then, $K_s$ (1.0 cm $h^{-1})$ was used as the fixed input parameter for the simulation of each models. The PSDs were estimated from the collected K(h) data by model simulation. In the simulation of Brooks-Corey parameter, the saturated hydraulic conductivity, $K_s$, played a role of scaling factor for unsaturated hydraulic conductivity, K(h) Changes of parameter b explained the shape of PSD curve of soil intimately, and a ${\alpha}_{BC}$ affected on the sensitivity of PSD curve. In the case of van Genuchten model, $K_s$ and ${\alpha}_{VG}$ played the role of scaling factor for a vertical axis and a horizontal axis, respectively. Parameter m described the shape of PSD curve and K(h) systematically. This study suggests that the new theoretical technique can be applied to the in situ prediction of PSD in undisturbed field soil.

Purification and Biological Characterization of Wild-type and Mutants of a Levan Fructotransferase from Microbacterium sp. AL-210 (Microbacterium sp. A-210이 생성하는 Levan fructotransferase의 정제 및 생물학적 특성에 관한 연구)

  • Hwang, Eun-Young;Jeong, Mi-Suk;Cha, Jae-Ho;Jang, Se-Bok
    • Journal of Life Science
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    • v.19 no.9
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    • pp.1218-1225
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    • 2009
  • Difractose anhydrides (DFAs) is studied as a sweetener for diabetics because of its structural property. DFAs have four types: DFA I, III, IV (degradation of levan) and V (degradation of inulin). Especially, DFA IV has been shown to enhance the absorption of calcium in experiments using rats. Levan fructotransferase is an enzyme for producing di-d-fructose-2,6':6,2-dianhydride (DFA IV). To identify structural characterization, we purified wild-type and mutants (D63A, D195N and N85S) of levan fructotransferase (LFTase) from Microbacterium sp. AL-210. These proteins were purified to apparent homogeneity by Ni-NTA affinity column, Q-sepharose ion exchange and gel filtration chromatography and detected by SDS-PAGE. They were also analyzed by circular dichroism (CD) measurements, JNET secondary structure prediction, activity measurements at various temperatures, and pH analysis. The optimum pH for the enzyme-catalyzed reaction was pH 7.5 and optimum temperature was observed at $55^{\circ}C$. Along with wild-type LFTase, mutants were analyzed by CD measurement, fluorescence analysis and differential scanning calorimetry (DSC). N85S showed less $\alpha$-helix and more $\beta$ strand than others. Also, N85S showed almost the same curve as wild-type in their steady-state fluorescence spectra, whereas mutant D63A and D195N showed higher intensity than wild-type. The amino acid sequence of wild-type LFTase was compared to the sequences of exo-inulinase from Aspergillus awamori, a plant fructan 1-exohydrolase from Cichorium intybus, and Thermotogo maritime (Tm) invertase and showed a high identity with Exo-inulinase from Aspergillus awamori.

Geographical Migration of Winter Barley in the Korean Peninsula under the RCP8.5 Projected Climate Condition (신 기후변화시나리오에 따른 한반도 내 겨울보리 재배적지 이동)

  • Kim, Dae-Jun;Kim, Jin-Hee;Roh, Jae-Hwan;Yun, Jin I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.14 no.4
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    • pp.161-169
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    • 2012
  • The RCP 8.5 scenario based temperature outlook (12.5 km resolution) was combined with high-definition gridded temperature maps (30 m grid spacing) across the Korean Peninsula in order to reclassify the cold hardiness zone for winter barley, a promising grain crop in the future under warmer winter conditions. Reference maps for the January minimum and mean temperature were prepared by applying the watershed-specific geospatial climate prediction schemes to the synoptic observations from 1981 to 2010 across North and South Korea. Decadal changes in the January minimum and mean temperatures projected by a regional version of RCP8.5 climate change scenario were prepared for the 2011-2100 period at 12.5 km grid spacing and were subsequently added to the reference maps, producing the 30 m resolution temperature surfaces for 9 decades from 2011 to 2100. A criterion for threshold temperature to grow winter barley safely in Korea was applied to the future temperature surfaces and the resulting maps were used to predict the production potential of 3 cultivar groups for the 9 future decades under the projected temperature conditions. By 2020s, hulled barley cultivars could be grown safely at the southern part of North Korea as well as the mountainous Gangwon province. Furthermore, most of South Korean rice paddies will be safe for growing naked barley after harvesting rice. Also, dual cropping systems such as 'winter-barley after rice' could be possible at most of the North Korean rice paddies by 2040s. Additional grain production in North Korea could increase up to 4 million tons per year if dual cropping systems can be fully operated, i.e., winter barley after rice at all lowlands and winter barley after maize or potato at all uplands.

Analysis of Environmental Design Data for Growing Pleurotus ervngii (큰 느타리버섯 재배사의 환경설계용 자료 분석)

  • Yoon, Yong-Cheol;Suh, Won-Myung;Lee, In-Bok
    • Journal of Bio-Environment Control
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    • v.14 no.2
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    • pp.95-105
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    • 2005
  • This study was carried out to file up using effect and requirement of energy for environmental design data of Pleurotus eryngii growing houses. Heating and cooling Degree-Hour (D-H) were calculated and compared for. some Pleurotus eryngii growing houses of sandwich-panel (permanent) o. arch-roofed(simple) type structures modified and suggested through field survey and analysis. Also thermal resistance (R-value) was calculated for the heat insulating and covering materials of the permanent and simple-type, which were made of polyurethane or polystyrene panel and $7\~8$ layers heat conservation cover wall. The variations of heating and cooling D-H simulated for Jinju area was nearly linearly proportional to the setting inside temperatures. The variations of cooling D-H was much more sensitive than those of heating D-H. Therefore, it was expected that the variations of required energy in accordance with setting temperature or actual temperature maintained inside of the cultivation house could be estimated and also the estimated results of heating and cooling D-H could be effectively used far the verification of environmental simulation as well as for the calculation of required energy amounts. When the cultivation floor areas are all equal, panel type houses to be constructed by various combinations of materials were found to by far more effective than simple type pipe house in the aspect of energy conservation maintenance except some additional cost invested initially. And also the energy effectiveness of multi-span house compared to single span together with the prediction of energy requirement depending on the level insulated for the wall and roof area could be estimated. Additionally, structural as well as environmental optimizations are expected to be possible by calculating periodical and/or seasonal energy requirements for those various combinations of insulation level and different climate conditions, etc.

Prediction of patent lifespan and analysis of influencing factors using machine learning (기계학습을 활용한 특허수명 예측 및 영향요인 분석)

  • Kim, Yongwoo;Kim, Min Gu;Kim, Young-Min
    • Journal of Intelligence and Information Systems
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    • v.28 no.2
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    • pp.147-170
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    • 2022
  • Although the number of patent which is one of the core outputs of technological innovation continues to increase, the number of low-value patents also hugely increased. Therefore, efficient evaluation of patents has become important. Estimation of patent lifespan which represents private value of a patent, has been studied for a long time, but in most cases it relied on a linear model. Even if machine learning methods were used, interpretation or explanation of the relationship between explanatory variables and patent lifespan was insufficient. In this study, patent lifespan (number of renewals) is predicted based on the idea that patent lifespan represents the value of the patent. For the research, 4,033,414 patents applied between 1996 and 2017 and finally granted were collected from USPTO (US Patent and Trademark Office). To predict the patent lifespan, we use variables that can reflect the characteristics of the patent, the patent owner's characteristics, and the inventor's characteristics. We build four different models (Ridge Regression, Random Forest, Feed Forward Neural Network, Gradient Boosting Models) and perform hyperparameter tuning through 5-fold Cross Validation. Then, the performance of the generated models are evaluated, and the relative importance of predictors is also presented. In addition, based on the Gradient Boosting Model which have excellent performance, Accumulated Local Effects Plot is presented to visualize the relationship between predictors and patent lifespan. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the evaluation reason of individual patents, and discuss applicability to the patent evaluation system. This study has academic significance in that it cumulatively contributes to the existing patent life estimation research and supplements the limitations of existing patent life estimation studies based on linearity. It is academically meaningful that this study contributes cumulatively to the existing studies which estimate patent lifespan, and that it supplements the limitations of linear models. Also, it is practically meaningful to suggest a method for deriving the evaluation basis for individual patent value and examine the applicability to patent evaluation systems.

Improving Usage of the Korea Meteorological Administration's Digital Forecasts in Agriculture: I. Correction for Local Temperature under the Inversion Condition (기상청 동네예보의 영농활용도 증진을 위한 방안: I. 기온역전조건의 국지기온 보정)

  • Kim, Soo-Ock;Kim, Dae-Jun;Kim, Jin-Hee;Yun, Jin I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.15 no.2
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    • pp.76-84
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    • 2013
  • An adequate downscaling of the official forecasts of Korea Meteorological Administration (KMA) is a prerequisite to improving the value and utility of agrometeorological information in rural areas, where complex terrain and small farms constitute major features of the landscape. In this study, we suggest a simple correction scheme for scaling down the KMA temperature forecasts from mesoscale (5 km by 5 km) to the local scale (30 m by 30 m) across a rural catchment, especially under temperature inversion conditions. The study area is a rural catchment of $50km^2$ area with complex terrain and located on a southern slope of Mountain Jiri National Park. Temperature forecasts for 0600 LST on 62 days with temperature inversion were selected from the fall 2011-spring 2012 KMA data archive. A geospatial correction scheme which can simulate both cold air drainage and the so-called 'thermal belt' was used to derive the site-specific temperature deviation across the study area at a 30 m by 30 m resolution from the original 5 km by 5 km forecast grids. The observed temperature data at 12 validation sites within the study area showed a substantial reduction in forecast error: from ${\pm}2^{\circ}C$ to ${\pm}1^{\circ}C$ in the mean error range and from $1.9^{\circ}C$ to $1.6^{\circ}C$ in the root mean square error. Improvement was most remarkable at low lying locations showing frequent cold pooling events. Temperature prediction error was less than $2^{\circ}C$ for more than 80% of the observed inversion cases and less than $1^{\circ}C$ for half of the cases. Temperature forecasts corrected by this scheme may accelerate implementation of the freeze and frost early warning service for major fruits growing regions in Korea.