• Animal Bioscience
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• v.34 no.3_spc
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• pp.434-442
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• 2021

Objective: This study aims to evaluate the influence of dietary flavonoids on the growth performance, blood and intestinal profiles, and carcass characteristics of broilers by employing a meta-analysis method. Methods: A database was built from published studies which have reported on the addition of various levels of flavonoids from herbs into broiler diets and then monitored growth performance, blood constituents, carcass proportion and small intestinal morphology. A total of 42 articles were integrated into the database. Several forms of flavonoids in herbs were applied in the form of unextracted and crude extracts. The database compiled was statistically analyzed using mixed model methodology. Different studies were considered as random effects, and the doses of flavonoids were treated as fixed effects. The model statistics used were the p-values and the Akaike information criterion. The significance of an effect was stated when its p-value was <0.05. Results: Dietary flavonoids increased (quadratic pattern; p<0.05) the average daily gain of broilers in the finisher phase. There was a reduction (p<0.01) in the feed conversion ratio of the broilers both in the starter (linear pattern) and finisher phases (quadratic pattern). The mortality rate tended to decrease linearly (p<0.1) with the addition of flavonoids, while the carcass parameter was generally not influenced. A reduction (p<0.001) in cholesterol and malondialdehyde concentrations (both linearly) was observed, while super oxide dismutase activity increased linearly (p<0.001). Increasing the dose of flavonoids increased (p<0.01) the villus height (VH) and villus height and crypt depth (VH:CD) ratio (p<0.05) in the duodenum. Similarly, the VH:CD ratio was elevated (p<0.001) in the jejunum following flavonoid supplementation. Conclusion: Increasing levels of flavonoids in broilers diet leads to an improvement in growth performance, blood constituents, carcass composition and small intestinal morphology.

• Journal of Animal Science and Technology
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• v.55 no.5
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• pp.389-398
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• 2013

This study was conducted to investigate the genetic relationships among four reproductive traits. Data for this study were 7616 records from 1910 Landrace (L) and 10,454 records from 2283 Yorkshire (Y) in a closed nucleus swine herd. Traits considered on this study were gestation length (GL), total number of piglets born (TNB), wean to first service (WFS), and number of stillborn per litter (NSB). Heritabilities and genetic correlations were estimated by using the Bayesian inferences via Gibbs sampling in a four trait linear-threshold repeatability animal mixed model by designating NSB as a categorical trait in the L and Y purebred populations. Effects on the statistical model were considered for parity, contemporary group as fixed and service sire, permanent environmental, animal additive genetic effects as random. Estimates of heritability were 0.21, 0.23, 0.16, and 0.09 for GL, WFS, TNB, and NSB in the L population and 0.35, 0.16, 0.14 and 0.10 for corresponding traits in the Y population, respectively. Genetic correlation for GL was -0.59 and -0.28 with TNB and -0.58 and -0.17 with NSB in the L and Y populations, respectively. The NSB was positively correlated with TNB in the L and Y populations in genetic and environmental aspects. Therefore, the NSB should be taken into account in selecting sows for improving prolificacy of dam line breeding swine stock.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.8 no.2
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• pp.45-51
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• 1990

DEM must have a high accuracy against the actual topographic model. A model which can compute heights responding to random plane position by using of the topographic data and interpolation must be constructed. Interpolation affected by the accuraccy of the observations included noise, which affected by the slop and curvature weight. Data smoothing is a method to reduce the noise. Average declination and area ratio are variable which result similarity in according to slope. But in local area, area ratio well shows a local change. This study try to classify the terrain by the declination to analysis the effects of the declination and curvature weights, and then to represent the most probable model. The result are following : In terrain classification by the slop, p16 and p24 were fitted in the plane surface fit p16 and S in the varying surface, and S and p24 in the irregular surface in classification by curvature, p24 and S were fitted in the plane or varying surface, and p16 in the irregular surface In case of hybrid, p16, p24 and S are fitted in the plane, varying and irregular surface respectively. Smoothing is the most effective in case of slope of 50 persentage and of curvature weight of 0.0015.

• Wind and Structures
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• v.10 no.4
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• pp.367-382
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• 2007

A nonlinear numerical method was developed to assess the stability of suspension bridge catwalks under a wind load. A section model wind tunnel test was used to obtain a catwalk's aerostatic coefficients, from which the displacement-dependent wind loads were subsequently derived. The stability of a suspension bridge catwalk was analyzed on the basis of the geometric nonlinear behavior of the structure. In addition, a full model test was conducted on the catwalk, which spanned 960 m. A comparison of the displacement values between the test and the numerical simulation shows that a numerical method based on a section model test can be used to effectively and accurately evaluate the stability of a catwalk. A case study features the stability of the catwalk of the Runyang Yangtze suspension bridge, the main span of which is 1490 m. Wind can generally attack the structure from any direction. Whenever the wind comes at a yaw angle, there are six wind load components that act on the catwalk. If the yaw angle is equal to zero, the wind is normal to the catwalk (called normal wind) and the six load components are reduced to three components. Three aerostatic coefficients of the catwalk can be obtained through a section model test with traditional test equipment. However, six aerostatic coefficients of the catwalk must be acquired with the aid of special section model test equipment. A nonlinear numerical method was used study the stability of a catwalk under a yaw wind, while taking into account the six components of the displacement-dependent wind load and the geometric nonlinearity of the catwalk. The results show that when wind attacks with a slight yaw angle, the critical velocity that induces static instability of the catwalk may be lower than the critical velocity of normal wind. However, as the yaw angle of the wind becomes larger, the critical velocity increases. In the atmospheric boundary layer, the wind is turbulent and the velocity history is a random time history. The effects of turbulent wind on the stability of a catwalk are also assessed. The wind velocity fields are regarded as stationary Gaussian stochastic processes, which can be simulated by a spectral representation method. A nonlinear finite-element model set forepart and the Newmark integration method was used to calculate the wind-induced buffeting responses. The results confirm that the turbulent character of wind has little influence on the stability of the catwalk.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.231-236
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• 2013

Background: Published data regarding the association between xeroderma pigmentosum group D (XPD) Lys751Gln and Asp312Asn polymorphisms and gastric cancer susceptibility havew been inconclusive. This meta-analysis was therefore performed toobtain a more precise estimation of any relationship. Materials and Methods: A comprehensive literature search was conducted to identify all case-control studies of Lys751Gln and Asp312Asn polymorphisms and susceptibility to gastric cancer. Summary odds ratios (ORs) and its 95% confidence intervals (95% CIs) were calculated using a random-effects model with the software STATA (version10.0). Results: A total of 12 case-control studies including 3,147 cases and 4,736 controls were included. Overall, no significant associations were found in some models (for Lys751Gln: Lys/Gln vs Lys/Lys: OR=1.144, 95% CI=0.851-1.541, Gln/Gln vs Lys/Lys: OR=1.215, 95% CI = 0.740-1.955, dominant model: OR=1.137, 95% CI=0.818-1.582; recessive model: OR=1.123, 95% CI=0.765-1.650; for Asp312Asn: Asp/Asn vs Asp/Asp: OR=1.180, 95% CI=0.646-2.154, dominant model: OR=1.380, 95% CI = 0.812-2.346), but significantly elevated susceptibility was found for Asp312Asn polymorphism in some models (Asn/Asn vs Asp/Asp: OR=2.045, 95% CI=1.254-3.335, recessive model: OR=1.805, 95% CI =1.219-2.672), for the additive model, the XPD Lys751Gln and Asp312Asn polymorphisms were not significantly associated with gastric cancer susceptibility. In stratified analyses, significantly elevated susceptibility was found for some models in the Chinese population. Conclusion: This meta-analysis suggested the XPD Asp312Asn polymorphism might be a potential biomarker of gastric cancer susceptibility in overall population, while both XPD Lys751Gln and Asp312Asn polymorphisms might be risk factors of gastric cancer susceptibility in Chinese.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.481-493
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• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• The Journal of Korean Academy of Sensory Integration
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• v.18 no.1
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• pp.56-72
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• 2020

Objective : The purpose is to analyze the effects of parent training interventions in reducing the symptoms of Attention Deficit Hyperactivity Disorder (ADHD) and to provide a basis for the effects. Methods : We collected literature published in international academic journals from 2009 to 2019 through ProQuest and Scopus databases. The search key terms were (ADHD OR Attention Deficit Hyperactivity Disorder) AND (Parent OR Mother OR Father) AND (Training OR Program OR Therapy OR Intervention) AND (Randomized OR Randomised OR Randomly). The PEDro scale was used to evaluate the quality of the studies, and a meta-analysis was conducted through Comprehensive Meta-Analysis 3.0. Results : Of 628 studies that we reviewed, 20 were eligible for inclusion. of parental training interventions for children with ADHD appeared close to a medium effect size while parent-child interventions (0.639) appeared to have a medium to large effect size. Oppositional defiant behavior and conduct disorder (0.737) in children and children's emotions (0.679) appeared close to a large effect size. ADHD symptoms hyperactivity and impulsivity (0.590) and child behavior (0.521) appeared to be over a medium effect size. We chose a random-effects model since heterogeneity tests showed significant results. Conclusion : We were able to confirm the effects of parent training interventions on the symptoms of children with ADHD. This will be used as evidence to provide a clinical basis for occupational therapists. More research related to parental training interventions should be carried out to ensure better reporting in the future.

• Communications of Mathematical Education
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• v.34 no.3
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• pp.325-354
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• 2020

This study utilized longitudinal data from the 2013 year (Secondary Middle School) to 2017 year (Secondary High School) of the Seoul Education Termination Study. Using the latent growth model and the piecewise growth model, we investigated the changes in mathematics academic achievement, internal factors(self-concept, self-control, self-assessment of life satisfaction), and external factors(school climate, guardians) as students' grades increased, and examined whether internal factors and external factors influence the changes in mathematics academic achievement. We examined whether internal and external factors influence the change in academic achievement. As a result of analysis, it was found that mathematics academic achievement remained unchanged from the first grade of middle school to the second grade of middle school, and steadily increased from the second grade of middle school to the first grade of high school, and then decreased slightly in the second grade of high school. The internal and external factors had little change. It has been found that self-concept, self-control as internal factors, and school climate as external factors influence changes in mathematics academic achievement.

• 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.

• Korean Journal of Remote Sensing
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• v.21 no.6
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• pp.445-456
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• 2005

The land surface parameters should be determined with sufficient accuracy, because these play an important role in climate change near the ground. As the surface reflectance presents strong anisotropy, off-nadir viewing results a strong dependency of observations on the Sun - target - sensor geometry. They contribute to the random noise which is produced by surface angular effects. The principal objective of the study is to provide a database of accurate surface reflectance eliminated the angular effects from MODIS 250m reflective channel data over Korea. The MODIS (Moderate Resolution Imaging Spectroradiometer) sensor has provided visible and near infrared channel reflectance at 250m resolution on a daily basis. The successive analytic processing steps were firstly performed on a per-pixel basis to remove cloudy pixels. And for the geometric distortion, the correction process were performed by the nearest neighbor resampling using 2nd-order polynomial obtained from the geolocation information of MODIS Data set. In order to correct the surface anisotropy effects, this paper attempted the semiempirical kernel-driven Bi- directional Reflectance Distribution Function(BRDF) model. The algorithm yields an inversion of the kernel-driven model to the angular components, such as viewing zenith angle, solar zenith angle, viewing azimuth angle, solar azimuth angle from reflectance observed by satellite. First we consider sets of the model observations comprised with a 31-day period to perform the BRDF model. In the next step, Nadir view reflectance normalization is carried out through the modification of the angular components, separated by BRDF model for each spectral band and each pixel. Modeled reflectance values show a good agreement with measured reflectance values and their RMSE(Root Mean Square Error) was totally about 0.01(maximum=0.03). Finally, we provide a normalized surface reflectance database consisted of 36 images for 2001 over Korea.