Yield prediction model for mixed pasture was developed with a shortage that the relationship between dry matter yield (DMY) and days of summer depression (DSD) was not properly reflected in the model in the previous research. Therefore, this study was designed to eliminate the data of the regions with distinctly different climatic conditions and then investigate their relationships DMY and DSD using the data in each region separately of regions with distinct climatic characteristics and classify the data based on regions for further analysis based on the previous mixed pasture prediction model. The data set used in the research kept 582 data points from 11 regions and 41 mixed pasture types. The relationship between DMY and DSD in each region were analyzed through scatter plot, correlation analysis and multiple regression analysis in each region separately. In the statistical analysis, DMY was taken as the response variable and 5 climatic variables including DSD were taken as explanatory variables. The results of scatter plot showed that negative correlations between DMY and DSD were observed in 7 out of 9 regions. Therefore, it was confirmed that analyzing the relationship between DMY and DSD based on each region is necessary and 5 regions were selected (Hwaseong, Suwon, Daejeon, Siheung and Gwangju) since the data size in these regions is large enough to perform the further statistical analysis based on large sample approximation theory. Correlation analysis showed that negative correlations were found between DMY and DSD in 3 (Hwaseong, Suwon and Siheung) out of the 5 regions, meanwhile the negative relationship in Hwaseong was confirmed through multiple regression analysis. Therefore, it was concluded that the interpretability of the yield prediction model for mixed pasture could be improved based on constructing the models using the data from each region separately instead of using the pooled data from different regions.

This study was aimed to find yield prediction model of Italian ryegrass using climate big data and geographic information. After that, mapping the predicted yield results using Geographic Information System (GIS) as follows; First, forage data were collected; second, the climate information, which was matched with forage data according to year and location, was gathered from the Korean Metrology Administration (KMA) as big data; third, the climate layers used for GIS were constructed; fourth, the yield prediction equation was estimated for the climate layers. Finally, the prediction model was evaluated in aspect of fitness and accuracy. As a result, the fitness of the model (R2) was between 27% to 95% in relation to cultivated locations. In Suwon (n=321), the model was; DMY = 158.63AGD –8.82AAT +169.09SGD - 8.03SAT +184.59SRD -13,352.24 (DMY: Dry Matter Yield, AGD: Autumnal Growing Days, SGD: Spring Growing Days, SAT: Spring Accumulated Temperature, SRD: Spring Rainfall Days). Furthermore, DMY was predicted as 9,790±120 (kg/ha) for the mean DMY(9,790 kg/ha). During mapping, the yield of inland areas were relatively greater than that of coastal areas except of Jeju Island, furthermore, northeastern areas, which was mountainous, had lain no cultivations due to weak cold tolerance. In this study, even though the yield prediction modeling and mapping were only performed in several particular locations limited to the data situation as a startup research in the Republic of Korea.

A class of phenolphthalein anilide based poly(ethersulfone) (PES) block copolymers containing pendent quaternary ammonium (QA) groups was prepared as anion exchange membranes by reaction involving nucleophilic substitution, benzylic bromination, quaternization and anion exchange with hydroxide ions. Hexafluorobenzene (HFB) was utilized as a linkage group between the hydrophobic and hydrophilic oligomer blocks. Nano-phase separated membrane morphology due to block structure of poly (ethersulfone) serves for better management of absorbed water for higher hydroxide conductivity with good thermal, and dimensional stability. The water uptake, swelling ratio, conductivity, and chemical stability of the copolymer membranes were comparatively investigated.

The objective of this study was to select a model showing high-levels of interpretability which is high in R-squared value in terms of predicting the yield in the mixed pasture using the factors of fertilization, seeding rate and years after pasture establishment in steps, as well as the climate as a basic factor. The processes of constructing the yield prediction model for the mixed pasture were performed in the sequence of data collection (forage and climatic data), preparation, analysis, and model construction. Through this process, six models were constructed after considering climatic variables, fertilization management, seeding rates, and periods after pasture establishment years in steps, thereafter the optimum model was selected through considering the coincidence of the models to the forage production theories. As a result, Model VI (R squared = 53.8%) including climatic variables, fertilization amount, seeding rates, and periods after pasture establishment was considered as the optimum yield prediction model for mixed pastures in South Korea. The interpretability of independent variables in the model were decreased in the sequence of climatic variables(24.5%), fertilization amount(17.8%), seeding rates(10.7%), and periods after pasture establishment(0.8%). However, it is necessary to investigate the reasons of positive correlation between dry matter yield and days of summer depression (DSD) by considering cultivated locations and using other cumulative temperature related variables instead of DSD. Meanwhile the another research about the optimum levels of fertilization amounts and seeding rates is required using the quadratic term due to the certain value-centered distribution of these two variables

목적: 이 연구의 목적은 고교배구 선수들의 자기결정성 동기와 집단효능감 및 팀 응집력의 관계를 규명하는 것이 다. 방법: 2022년도 대한배구협회에 등록된 전국 남녀 고등부 배구선수 422명을 대상으로 스포츠 동기, 집단효능 감, 팀 응집력 설문지를 배포하여 자료를 수집한 뒤 기술통계, 신뢰도 분석, 요인 분석, 상관 분석 및 회귀 분석 을 실시하였다. 결과: 자기 결정성 동기, 집단효능감의 하위 요인은 팀 응집력의 하위요인과 대부분 유의한 상관 관계가 있는 것으로 나타났으며, 팀 응집력은 주로 집단 효능감의 하위요인인 집단 효능과 개인 효능 그리고 자 기결정성 동기의 하위요인인 내재 조절에 의해서 정적으로 영향을 받는 것으로 나타났다. 결론: 팀 응집력에 대 한 자기결정성과 집단 효능감의 역할을 파악했으며, 팀 퍼포먼스를 향상 시키기 위한 동기 심리와 사회인지 심리 변수 활용에 대해서 제언하였다.

본 연구에서는 실험을 통하여 자기치유 재료 혼입 모르타르 보의 자기치유 성능을 평가하였다. 실험에는 일반 모르타르 보 실험체와 자기치유 모르타르 보 실험체가 사용되었으며, 모르타르의 압축강도, 내력 및 균열의 자기치유 효과를 비교하여 자기치유 성능을 평가하였다. 실험결과 자기치유 재료를 혼입한 모르타르의 압축강도가 일반 모르타르의 압축강도보다 작았지만 28일 압축강도에 대한 118일 압축강도 비율은 동일하게 나타났다. 실험체의 내력은 재령일이 길어질수록 증가하는 경향을 나타냈다. 일반 모르타르 실험체는 균열이 발생할 경우 재령일이 증가하여도 하중은 회복되지 않았으나 자기치유 모르타르 실험체의 경우 반응 생성물의 영향으로 내력이 다소 회복되는 경향을 나타냈다. 균열폭은 두 종류의 실험체 모두 치유기간이 지난 후 감소하는 경향을 보였으나 자기치유 모르타르 실험체에서만 반응 생성물이 관찰되었다.

최근 지진의 발생 빈도가 잦아지면서 고강도 내진 철근에 대한 관심이 급증하였다. 그러나 현재 콘크리트구조 학회기준 (2017)에서는 철근콘크리트 부재의 전단철근의 항복강도를 500MPa로 제한하고 있다. 이 논문에서는 이러한 설계기준항복강도 제한을 확장하기 위해 고강도 내진 철근을 사용한 철근콘크리트 보의 실험을 수행하였다. 실험에는 항복강도가 400MPa, 500MPa, 700MPa인 전단철근이 사용되었으며 전단철근의 배근간격을 변수로 하여 철근비에 따른 철근콘크리트 보의 전단거동을 비교하였다. 실험결과 철근량과 철근의 항복강도가 증가할수록 전단강도비가 감소하는 경향이 나타났다.