• 제목/요약/키워드: selection index

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Ferulic Acid Content of Barley and Wheat Grains and Head Blight Resistance (맥류 종자의 페룰산(ferulic acid) 함량과 붉은곰팡이 저항성)

  • Baek, Seul Gi;Kim, Sosoo;Jang, Ja Yeong;Kim, Jeomsoon;Lee, Theresa
    • Research in Plant Disease
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    • v.26 no.4
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    • pp.250-255
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    • 2020
  • In order to find if a ferulic acid (FA) can be used as a selection index in cereal breeding for resistance to head blight and mycotoxin production, we analyzed FA in the grains of 80 cultivars of barley, rice, and wheat. FA content ranged 1.66-2.77 mg/g in barley (n=20), 0.56-1.53 mg/g in wheat (n=40), and 0.91-2.13 mg/g in rice (n=20). Among these, 7 cultivars each of barley and wheat with different FA content were tested for head blight and mycotoxin production by 2 Fusarium graminearum and 2 F. asiaticum strains. Mean pathogenicity of the wheat cultivars was significantly less than that of barley with higher FA and among wheat cultivars, there was no correlation between FA content and pathogenicity. Mycotoxin production was also lower in the wheat than in the barley as pathogenicity. However, pathogenicity and toxins produced by F. asiaticum were negatively correlated with FA content in barley. These results indicate that FA is not a resistance factor to head blight by F. asiaticum and F. graminearum or its mycotoxin production in barley and wheat.

Analysis of the Priority of Evaluation Criteria and Detailed Index for Selecting Street Trees (가로수 선정 평가기준과 세부지표의 중요도 분석)

  • Kim, Min Kyung
    • Journal of the Korean Institute of Landscape Architecture
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    • v.49 no.1
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    • pp.42-53
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    • 2021
  • Street trees improve the cityscape and air quality, reduce heat islands, and create wildlife habitats. Hence, they are essential parts of a city's green infrastructure. Therefore, several trees that are well adapted to the urban environment were planted. However, this caused the problem of simple trees being planted around the world. This study is to select more various street trees. To accomplish this, evaluation criteria and detailed indexes were created. The importance was indicated through the Analytic Hierarchy Process. For commercial roads, the priority of landscape characteristics is 0.2640, and among detailed indicators, the priority of shape is 0.1245. For work roads, the priority of landscape characteristics is 0.2496, and among detailed indicators, the priority of shape is 0.1177. For work roads, the priority of characteristics of civil service is 0.2250, and among detailed indicators, the priority of shape is 0.1177. For general roads, the priority of maintenance characteristics is 0.2479, and among detailed indicators, the priority of shape is 0.1062. For historical and cultural roads, the priority of regional characteristics is 0.3488, and among detailed indicators, the priority of regional characteristics is 0.1643. For ecological roads, the priority of ecosystem characteristics is 0.3488, and among detailed indicators, the priority of the diversity of species is 0.1643. For automotive-only roads, the priority of the ecosystem characteristics is 0.4639, and among detailed indicators, the priority of reducing emissions is 0.1643. This study will provide objective criteria for the selection of street trees.

Full-Endoscopic versus Minimally Invasive Lumbar Interbody Fusion for Lumbar Degenerative Diseases : A Systematic Review and Meta-Analysis

  • Son, Seong;Yoo, Byung Rhae;Lee, Sang Gu;Kim, Woo Kyung;Jung, Jong Myung
    • Journal of Korean Neurosurgical Society
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    • v.65 no.4
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    • pp.539-548
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    • 2022
  • Objective : Although full-endoscopic lumbar interbody fusion (Endo-LIF) has been tried as the latest alternative technique to minimally invasive transforaminal lumbar interobody fusion (MIS-TLIF) since mid-2010, the evidence is still lacking. We compared the clinical outcome and safety of Endo-LIF to MIS-TLIF for lumbar degenerative disease. Methods : We systematically searched electronic databases, including PubMed, EMBASE, and Cochrane Library to find literature comparing Endo-LIF to MIS-TLIF. The results retrieved were last updated on December 11, 2020. The perioperative outcome included the operation time, blood loss, complication, and hospital stay. The clinical outcomes included Visual analog scale (VAS) of low back pain and leg pain and Oswestry disability index (ODI), and the radiological outcome included pseudoarthosis rate with 12-month minimum follow-up. Results : Four retrospective observational studies and one prospective observational study comprising 423 patients (183 Endo-LIF and 241 MIS-TLIF) were included, and the pooled data analysis revealed low heterogeneity between studies in our review. Baseline characteristics including age and sex were not different between the two groups. Operation time was significantly longer in Endo-LIF (mean difference [MD], 23.220 minutes; 95% confidence interval [CI], 10.669-35.771; p=0.001). However, Endo-LIF resulted in less perioperative blood loss (MD, -144.710 mL; 95% CI, 247.941-41.478; p=0.023). Although VAS back pain at final (MD, -0.120; p=0.586), leg pain within 2 weeks (MD, 0.005; p=0.293), VAS leg pain at final (MD, 0.099; p=0.099), ODI at final (MD, 0.141; p=0.093) were not different, VAS back pain within 2 weeks was more favorable in the Endo-LIF (MD, -1.538; 95% CI, -2.044 to -1.032; p<0.001). On the other hand, no statistically significant group difference in complication rate (relative risk [RR], 0.709; p=0.774), hospital stay (MD, -2.399; p=0.151), and pseudoarthrosis rate (RR, 1.284; p=0.736) were found. Conclusion : Relative to MIS-TLIF, immediate outcomes were favorable in Endo-LIF in terms of blood loss and immediate VAS back pain, although complication rate, mid-term clinical outcomes, and fusion rate were not different. However, the challenges for Endo-LIF include longer operation time which means a difficult learning curve and limited surgical indication which means patient selection bias. Larger-scale, well-designed study with long-term follow-up and randomized controlled trials are needed to confirm and update the results of this systematic review.

An Evaluation of the Importance of Major Indicators for Measuring the Level of Spatial Informatization in Local Governments (지방정부의 공간정보화 수준 측정을 위한 주요 지표의 중요도 평가)

  • Kim, Yeon-Seong;Seo, Won-Chan;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.5
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    • pp.985-994
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    • 2022
  • This study diagnoses the maturity level of local government's spatial information policy in the face of the digital transformation period. To this end, by using the stratification (AHP) analysis technique, for the spatial information expert group, the importance evaluation is performed along with the selection of measurement indicators of the level of spatial informatization. First, the current status and indicators in terms of spatial information policies of local governments are studied through theoretical considerations. In addition, by examining previous studies, differentiation from this study is presented. In this study, 3 indicators and 18 detailed items of spatial informatization level evaluation indicators could be selected. As a result of the evaluation, the overall importance ranking for the measurement index was 0.125 (12.5%) for the establishment and utilizations of GIS Systems provided by local governments, 0.109 (10.9%) for the quality management of basic spatial information, 0.107 (10.7%) for the establishment and utilization of its own spatial information. 0.073 (7.3%) for the collaboration and sharing within the institution, 0.071 (7.1%) for the operation of education and support system on spatial information, 0.065 (6.5%) for the securing a dedicated organization and professional human resources, and interest at the institutional level were derived in the order of 0.053 (5.3%). The results of this study are expected to be usefully utilized as basic data to evaluate the level of spatial information policies promoted by local governments. In addition, if the local government's spatial information policy is pursued centering on the major indicators derived from the study, it is expected that efficient policy operation will be possible.

Analysis of the Optimal Window Size of Hampel Filter for Calibration of Real-time Water Level in Agricultural Reservoirs (농업용저수지의 실시간 수위 보정을 위한 Hampel Filter의 최적 Window Size 분석)

  • Joo, Dong-Hyuk;Na, Ra;Kim, Ha-Young;Choi, Gyu-Hoon;Kwon, Jae-Hwan;Yoo, Seung-Hwan
    • Journal of The Korean Society of Agricultural Engineers
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    • v.64 no.3
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    • pp.9-24
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    • 2022
  • Currently, a vast amount of hydrologic data is accumulated in real-time through automatic water level measuring instruments in agricultural reservoirs. At the same time, false and missing data points are also increasing. The applicability and reliability of quality control of hydrological data must be secured for efficient agricultural water management through calculation of water supply and disaster management. Considering the characteristics of irregularities in hydrological data caused by irrigation water usage and rainfall pattern, the Korea Rural Community Corporation is currently applying the Hampel filter as a water level data quality management method. This method uses window size as a key parameter, and if window size is large, distortion of data may occur and if window size is small, many outliers are not removed which reduces the reliability of the corrected data. Thus, selection of the optimal window size for individual reservoir is required. To ensure reliability, we compared and analyzed the RMSE (Root Mean Square Error) and NSE (Nash-Sutcliffe model efficiency coefficient) of the corrected data and the daily water level of the RIMS (Rural Infrastructure Management System) data, and the automatic outlier detection standards used by the Ministry of Environment. To select the optimal window size, we used the classification performance evaluation index of the error matrix and the rainfall data of the irrigation period, showing the optimal values at 3 h. The efficient reservoir automatic calibration technique can reduce manpower and time required for manual calibration, and is expected to improve the reliability of water level data and the value of water resources.

Estimation of Genetic Parameters for Residual feed intake in Duroc pigs (두록 품종에서 잔류사료섭취량의 유전모수 추정)

  • Song, Na-Rae;Kim, Yong-Min;Kim, Doo-Wan;Sa, Soo-Jin;Kim, Ki-Hyun;Kim, Young-Hwa;Cho, Kyu-Ho;Do, Chang-hee;Hong, Joon-Ki
    • Journal of agriculture & life science
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    • v.50 no.1
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    • pp.147-153
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    • 2016
  • Residual feed intake(RFI), a linear index, is a trait derived from the difference between actual feed intake and that predicted on the basis of the requirements for maintenance of body weight and production. This study was conducted to estimate RFI genetic parameters of swine in Korea, and used 8,696 of productions data of Duroc swine species which were born from 2001 to 2014. Correlation between average daily gain and RFI breeding value has been investigated by negative correlation of -0.2(P>0.01). Estimates of heritability for RFI1(residual feed intake calculated from model average dily gain) and RFI2(residual feed intake calculated from model average dily gain and backfat) were 0.37 and 0.45. From the genetic parameter estimates found in this study, selection for low RFI in Duroc pigs has the potential to improve feed conversion ratio and reduce feed intake.

A Study on the Recovery Rate of Vegetation in Forest Fire Damage Areas Using Sentinel-2B Satellite Images (Sentinel-2B 위성 영상을 활용한 산불 피해지역 식생 회복률에 관한 연구)

  • Gumsung Cheon;Kwangil Cheon;Byung Bae Park
    • Journal of Environmental Impact Assessment
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    • v.32 no.6
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    • pp.463-472
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    • 2023
  • The amount of damage and the area of damage to forest fires are increasing globally, and the effectiveness analysis of the restoration method after the damage is performed insufficient. This study calculated the area of forest fire damage was calculated using Sentinel-2B satellite images and stack map and the intensity of forest fire damage is analyzed according to the forest type. In addition, the vegetation index was calculated using various wavelength bands. Based on the results, the vegetation resilience by the restoration method was quantitatively. As results, areas with a high proportion of coniferous forests suffered high intensity forest fire damage, and areas with a relatively high ratio of mixed and broad-leaved forests tended to have low forest fire damage. Also, artificial forests showed a recovery of about 92.7% compared to before forest fires and natural forests showed a recovery of about 99.6% from the result of analyzing vegetation resilience in artificial and natural forests after forest fires. Accordingly, it was confirmed that natural forests after forest fire damage had superior vegetation resilience compared to artificial forests. It can be proposed that this study is meaningful in providing important information for efficiently restoring the affected target site and the selection criteria for trees to reduce forest fire damage through the evaluation of vegetation resilience by the intensity of forest fire damage and restoration methods.

Development of Near Infrared Spectroscopy(NIRS) Equation of Crude Protein in Wheat Germplasm

  • Hyemyeong Yoon;Myung-Chul Lee;Yumi Choi;Myong-Jae Shin;Sejong Oh
    • Proceedings of the Plant Resources Society of Korea Conference
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    • 2020.08a
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    • pp.100-100
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    • 2020
  • Wheat is mainly composed of carbohydrate but it contains a moderate amount of protein, which gives a very useful characteristics to flour food such as the unique elasticity and stickiness of the dough. We developed a calibration equation for analyzing crude protein content using Near Infrared Spectroscopy to quick analyze the crude protein content of wheat germplasm stored in the National Agrobiodiversity Center, RDA, Korea. The 1,798 wheat germplasms were used to draw up the calibration formula. The crude protein's interval distribution of 1,798 wheat germplasms used for the calibration was 7.04-20.84%, the average content was 13.2%, and standard deviation was 2.6%. The germplasms distribution was composed of a suitable group for the preparation of the calibration formula because the content distribution was a normal, excluding the 13.0-15.5% content section. In order to verify the applicability of the NIRS prediction model, we measured the crude protein content of the 300 wheat germplasms that were not used for the calibration using both Kjeldahl analysis and NIR spectrum. The analysis value calculated using each method were statistically processed, and the test results and statistical indicators of the predictive model were compared. As a result, The R2 value of the optimized NIRS prediction model was 0.997, and the Standard error of Calibration value(SEC) was 0.132, and slope value was 1.000. With prediction model selection, compared to Kjeldahl method, R2 values were 0.994(Kjeldahl), 0.998(NIRS), and the SEC value were 0.191 and 0.132, respectively, comparing the statistical indices of the forecast model. And slope value were 1.013, 1.000, respectively. The analysis of crude protein content by the NIRS predictive model developed by each statistical index showing similar figures is judged to show a high degree of correlation with the Kjeldahl analysis. The proven calibration equation will be used to measure the crude protein content of wheat germplasms held by the National Agrobiodiversity Center, and by dividing the wheat germplasms by their use according to the crude protein content, it will provide useful information to relevant researchers.

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Assessment of Landslide Susceptibility in Jecheon Using Deep Learning Based on Exploratory Data Analysis (데이터 탐색을 활용한 딥러닝 기반 제천 지역 산사태 취약성 분석)

  • Sang-A Ahn;Jung-Hyun Lee;Hyuck-Jin Park
    • The Journal of Engineering Geology
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    • v.33 no.4
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    • pp.673-687
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    • 2023
  • Exploratory data analysis is the process of observing and understanding data collected from various sources to identify their distributions and correlations through their structures and characterization. This process can be used to identify correlations among conditioning factors and select the most effective factors for analysis. This can help the assessment of landslide susceptibility, because landslides are usually triggered by multiple factors, and the impacts of these factors vary by region. This study compared two stages of exploratory data analysis to examine the impact of the data exploration procedure on the landslide prediction model's performance with respect to factor selection. Deep-learning-based landslide susceptibility analysis used either a combinations of selected factors or all 23 factors. During the data exploration phase, we used a Pearson correlation coefficient heat map and a histogram of random forest feature importance. We then assessed the accuracy of our deep-learning-based analysis of landslide susceptibility using a confusion matrix. Finally, a landslide susceptibility map was generated using the landslide susceptibility index derived from the proposed analysis. The analysis revealed that using all 23 factors resulted in low accuracy (55.90%), but using the 13 factors selected in one step of exploration improved the accuracy to 81.25%. This was further improved to 92.80% using only the nine conditioning factors selected during both steps of the data exploration. Therefore, exploratory data analysis selected the conditioning factors most suitable for landslide susceptibility analysis and thereby improving the performance of the analysis.

Preoperative Prediction for Early Recurrence Can Be as Accurate as Postoperative Assessment in Single Hepatocellular Carcinoma Patients

  • Dong Ik Cha;Kyung Mi Jang;Seong Hyun Kim;Young Kon Kim;Honsoul Kim;Soo Hyun Ahn
    • Korean Journal of Radiology
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    • v.21 no.4
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    • pp.402-412
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    • 2020
  • Objective: To evaluate the performance of predicting early recurrence using preoperative factors only in comparison with using both pre-/postoperative factors. Materials and Methods: We retrospectively reviewed 549 patients who had undergone curative resection for single hepatcellular carcinoma (HCC) within Milan criteria. Multivariable analysis was performed to identify pre-/postoperative high-risk factors of early recurrence after hepatic resection for HCC. Two prediction models for early HCC recurrence determined by stepwise variable selection methods based on Akaike information criterion were built, either based on preoperative factors alone or both pre-/postoperative factors. Area under the curve (AUC) for each receiver operating characteristic curve of the two models was calculated, and the two curves were compared for non-inferiority testing. The predictive models of early HCC recurrence were internally validated by bootstrap resampling method. Results: Multivariable analysis on preoperative factors alone identified aspartate aminotransferase/platelet ratio index (OR, 1.632; 95% CI, 1.056-2.522; p = 0.027), tumor size (OR, 1.025; 95% CI, 0.002-1.049; p = 0.031), arterial rim enhancement of the tumor (OR, 2.350; 95% CI, 1.297-4.260; p = 0.005), and presence of nonhypervascular hepatobiliary hypointense nodules (OR, 1.983; 95% CI, 1.049-3.750; p = 0.035) on gadoxetic acid-enhanced magnetic resonance imaging as significant factors. After adding postoperative histopathologic factors, presence of microvascular invasion (OR, 1.868; 95% CI, 1.155-3.022; p = 0.011) became an additional significant factor, while tumor size became insignificant (p = 0.119). Comparison of the AUCs of the two models showed that the prediction model built on preoperative factors alone was not inferior to that including both pre-/postoperative factors {AUC for preoperative factors only, 0.673 (95% confidence interval [CI], 0.623-0.723) vs. AUC after adding postoperative factors, 0.691 (95% CI, 0.639-0.744); p = 0.0013}. Bootstrap resampling method showed that both the models were valid. Conclusion: Risk stratification solely based on preoperative imaging and laboratory factors was not inferior to that based on postoperative histopathologic risk factors in predicting early recurrence after curative resection in within Milan criteria single HCC patients.