• Title/Summary/Keyword: Low correlation

Search Result 5,738, Processing Time 0.039 seconds

Analysis of Thermal Environment Characteristics by Spatial Type using UAV and ENVI-met (UAV와 ENVI-met을 활용한 공간 유형별 열환경 특성 분석)

  • KIM, Seoung-Hyeon;PARK, Kyung-Hun;LEE, Su-Ah;SONG, Bong-Geun
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.25 no.1
    • /
    • pp.28-43
    • /
    • 2022
  • This study classified UAV image-based physical spatial types for parks in urban areas of Changwon City and analyzed thermal comfort characteristics according to physical spatial types by comparing them with ENVI-met thermal comfort results. Physical spatial types were classified into four types according to UAV-based NDVI and SVF characteristics. As a result of ENVI-met thermal comfort, the TMRT difference between the tree-dense area and other areas was up to 30℃ or more, and it was 19. 6℃ at 16:00, which was the largest during the afternoon. As a result of analyzing UAV-based physical spatial types and thermal comfort characteristics by time period, it was confirmed that the physical spatial types with high NDVI and high SVF showed a similar to thermal comfort change patterns by time when using UAV, and the physical spatial types with dense trees and artificial structures showed a low correlation to thermal comfort change patterns by time when using UAV. In conclusion, the possibility of identifying the distribution of thermal comfort based on UAV images was confirmed for the spatial type consisting of open and vegetation, and the area adjacent to the trees was found to be more thermally pleasant than the open area. Therefore, in the urban planning stage, it is necessary to create an open space in consideration of natural covering materials such as grass and trees, and when using artificial covering materials, it is judged that spatial planning should be done considering the proximity to trees and buildings. In the future, it is judged that it will be possible to quickly and accurately identify urban climate phenomena and establish urban planning considering thermal comfort through ground LIDAR and In-situ measurement-based UAV image correction.

Evaluation of Temperature and Precipitation over CORDEX-EA Phase 2 Domain using Regional Climate Model HadGEM3-RA (HadGEM3-RA 지역기후모델을 이용한 CORDEX 동아시아 2단계 지역의 기온과 강수 모의 평가)

  • Byon, Jae-Young;Kim, Tae-Jun;Kim, Jin-Uk;Kim, Do-Hyun
    • Journal of the Korean earth science society
    • /
    • v.43 no.3
    • /
    • pp.367-385
    • /
    • 2022
  • This study evaluates the temperature and precipitation results in East Asia simulated from the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) developed by the UK Met Office. The HadGEM3-RA is conducted in the Coordinated Regional climate Downscaling Experiment-East Asia (CORDEX-EA) Phase II domain for 15 year (2000-2014). The spatial distribution of rainbands produced from the HadGEM3-RA by the summer monsoon is in good agreement with the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of water resources (APRODITE) data over the East Asia. But, precipitation amount is overestimated in Southeast Asia and underestimated over the Korean Peninsula. In particular, the simulated summer rainfall and APRODITE data show the least correlation coefficient and the maximum value of root mean square error in South Korea. Prediction of temperature in Southeast Asia shows underestimation with a maximum error during winter season, while it appears the largest underestimation in South Korea during spring season. In order to evaluate local predictability, the time series of temperature and precipitation compared to the ASOS data of the Seoul Meteorological Station is similar to the spatial average verification results in which the summer precipitation and winter temperature underestimate. Especially, the underestimation of the rainfall increases when the amounts of precipitation increase in summer. The winter temperature tends to underestimate at low temperature, while it overestimates at high temperature. The results of the extreme climate index comparison show that heat wave is overestimated and heavy rainfall is underestimated. The HadGEM3-RA simulated with a horizontal resolution of 25 km shows limitations in the prediction of mesoscale convective system and topographic precipitation. This study indicates that improvement of initial data, horizontal resolution, and physical process are necessary to improve predictability of regional climate model.

An Empirical Study on the Improvement of In Situ Soil Remediation Using Plasma Blasting, Pneumatic Fracturing and Vacuum Suction (플라즈마 블라스팅, 공압파쇄, 진공추출이 활용된 지중 토양정화공법의 정화 개선 효과에 대한 실증연구)

  • Jae-Yong Song;Geun-Chun Lee;Cha-Won Kang;Eun-Sup Kim;Hyun-Shic Jang;Bo-An Jang;Yu-Chul Park
    • The Journal of Engineering Geology
    • /
    • v.33 no.1
    • /
    • pp.85-103
    • /
    • 2023
  • The in-situ remediation of a solidified stratum containing a large amount of fine-texture material like clay or organic matter in contaminated soil faces limitations such as increased remediation cost resulting from decreased purification efficiency. Even if the soil conditions are good, remediation generally requires a long time to complete because of non-uniform soil properties and low permeability. This study assessed the remediation effect and evaluated the field applicability of a methodology that combines pneumatic fracturing, vacuum extraction, and plasma blasting (the PPV method) to improve the limitations facing existing underground remediation methods. For comparison, underground remediation was performed over 80 days using the experimental PPV method and chemical oxidation (the control method). The control group showed no decrease in the degree of contamination due to the poor delivery of the soil remediation agent, whereas the PPV method clearly reduced the degree of contamination during the remediation period. Remediation effect, as assessed by the reduction of the highest TPH (Total Petroleum Hydrocarbons) concentration by distance from the injection well, was uncleared in the control group, whereas the PPV method showed a remediation effect of 62.6% within a 1 m radius of the injection well radius, 90.1% within 1.1~2.0 m, and 92.1% within 2.1~3.0 m. When evaluating the remediation efficiency by considering the average rate of TPH concentration reduction by distance from the injection well, the control group was not clear; in contrast, the PPV method showed 53.6% remediation effect within 1 m of the injection well, 82.4% within 1.1~2.0 m, and 68.7% within 2.1~3.0 m. Both ways of considering purification efficiency (based on changes in TPH maximum and average contamination concentration) found the PPV method to increase the remediation effect by 149.0~184.8% compared with the control group; its average increase in remediation effect was ~167%. The time taken to reduce contamination by 80% of the initial concentration was evaluated by deriving a correlation equation through analysis of the TPH concentration: the PPV method could reduce the purification time by 184.4% compared with chemical oxidation. However, the present evaluation of a single site cannot be equally applied to all strata, so additional research is necessary to explore more clearly the proposed method's effect.

Evaluation of HbA1c Levels Via the Latex Immunoturbidimetric Method by Using Chemistry Autoanalyzer (자동화학분석기에서의 라텍스 면역비탁법의 Autolab HbA1c 평가)

  • Jo, Yongjun;Lee, So-young;Park, Hae-il;Kim, YeongSic;Lee, Jehoon;Kim, Yonggoo;Han, Kyungja
    • Laboratory Medicine Online
    • /
    • v.2 no.1
    • /
    • pp.10-14
    • /
    • 2012
  • Background: Measurement of HbA1c levels is widely used to diagnose diabetes mellitus and to evaluate and monitor plasma-glucose concentrations over 6-8 weeks. In this study, we evaluated the diagnostic performance of the newly developed latex immunoturbidimetric method by using Autolab HbA1c. Methods: We analyzed and compared the diagnostic performance of Autolab HbA1c with that of Toshiba 200FR between April 2009 and July 2009. According to guidelines (EP5-A2, EP6-P, EP9-A2) of the clinical and laboratory standards institute (CLSI), we compared linearity, precision and correlation of Autolab HbA1c with those of G7 (Tosoh Corp., Kyoto, Japan) by using high-performance liquid chromatography (HPLC) method. Results: Data obtained using Autolab HbA1c showed good linearity in mixtures of samples with low (3.1%) and high (15.1%) levels of HbA1c (r2=0.9997). In the analysis of within-run precision of the samples with HbA1c levels of 5.1% and 12.1%, the SDs were 0.04 and 0.06 and covariances of these samples were 0.8% and 0.5%, respectively. In the Deming regression model, the regression equation was as follows: Autolab HbA1c=1.0859×Tosoh HPLC-0.6957. Conclusions: In this study, Autolab HbA1c method showed better performance characteristics than Tosoh G7 did. In reference review, there was no interference of variant hemoglobin. The data acquisition time of Autolab HbA1c was lower than that of Tosoh G7. The advantages of Autolab HbA1c are that it can be used as an autoanlyzer in routine chemical analysis, it does not require pre-analytical treatment, and the samples are automatically treated with distilled water for hemolysis.

Space design Effect on Marketing ­ - Concentrating on B to B transaction - (공간 디자인이 마케팅에 미치는 영향 ­ - 전문전시회에서 B to B 거래중심으로 -)

  • Kim, Young Soo;Jeong, Dong Bin;Kim, Kyong Hoon
    • Korea Science and Art Forum
    • /
    • v.20
    • /
    • pp.147-158
    • /
    • 2015
  • This study made an approach to the industrial exhibition space, which is a medium of marketing communication, from the position of an enterprise and consumers through the output of Space Design, and conducted it with focus on B2B transactions among specialized exhibitions. In addition, this study inquired into what factors should be considered along with space design by interpreting the purpose of participating in the exhibition and space design of the enterprise which supply capital goods, elements, related technologies and materials, etc. This study aimed at drawing the direct/indirect effect, produced by space design, on the marketing by analyzing correlation between space design and participating enterprises' marketing. Despite the marketing effect of the exhibition, which was proved by preceding research results, the reality is that exhibition-participating expenses work as considerable burden on enterprises. Particularly, booth design, which is forming the most proportion among the participating expenses, was found to have insufficient influence on visitors due to the decline in its importance among diverse factors influencing visitor's decision to visit a booth. Regardless of the business category of participating enterprises in the exhibition, the standard of exhibits was ranked as the most important consideration factor in visiting a booth. Even by business category, the standard of booth design rarely had an influence on booth visit. Booth design had an affirmative influence on participating enterprise's preference, but its influence on product purchase or business talk & contact with a participating enterprise or price was found to be extremely low. It's difficult to judge marketing success or failure of an exhibition by the form and standard of booth design. Preferably, this study infers that it's necessary to put much weight on qualitative excellence of an exhibition, which consists of participation of an enterprise in possession of excellent technologies, exhibits with higher standards and high-quality visitors with purchasing power. This study suggests that it's more effective to set up the plan for expansion of participation in exhibition by optimally regulating the proportion of space design in participating expense to increase marketing effectiveness of an exhibition. The limitations of this study, analysis of which based on the visitors to an exhibition only, requires supplementation through the follow-up research work on participating enterprises in the exhibition.

Distribution of hazardous heavy metals in commercial herbal medicines classified by plant parts used in seoul (서울지역 유통한약재의 약용부위에 따른 유해중금속 분포)

  • Kim, Donggyu;Kim, Bogsoon;Han, Eunjung;Han, Changho;Kim, Oukhee;Choi, Byunghyun;Hwang, Insook;Chae, Youngzoo;Kim, Minyoung;Park, Seungkook
    • Analytical Science and Technology
    • /
    • v.22 no.6
    • /
    • pp.504-513
    • /
    • 2009
  • In this study, the safety of commercial herbal medicines was evaluated by determining concentration of hazardous heavy metals. 3,152 samples (244 types) purchased by individual packing unit from market in Seoul, were analyzed using ICP-MS and mercury analyzer. As a result, the content (mg $kg^{-1}$) of Pb was higher in the above-ground part (0.92) than underground part (0.43). But in case of As and Cd contents, there is slightly higher in the underground-parts (0.26, 0.13) than the above-ground parts (0.18, 0.08). There were many herbal medicines exceeding regulatory limits of Cd comparing with other metals. The levels of Hg seemed to be different between above-ground part(0.009) and underground part (0.008) but there was no sample exceeding tolerance limits. In the comparison of imported samples with domestic herbal medicines, it was shown that Pb, As, and Hg were measured highly in the imported ones, Cd was not significantly different (t-test, p<0.05). The significant correlation was observed between Pb and As (r=0.386, p<0.01) but there was no difference in other parts. The heavy metal contamination of herbal medicines measured in total amount of respective heavy metals (mg $kg^{-1}$) was high in Flos (6.241) and Caulis (2.238), and decreased in the order of Cortex (1.634), Herba (1.154), Perithecium (0.861), Rhizoma (0.828), Radix (0.825), Fructus (0.475), and was low in Semen (0.422) (ANOVA-test, p<0.05).

Spatial Autocorrelation and the Turnout of the Early Voting and Regular Voting: Analysis of the 21st General Election at Dong in Seoul (공간적 자기상관성과 관내사전투표와 본투표의 투표율: 제21대 총선 서울시 동별 분석)

  • Lim, Sunghack
    • Korean Journal of Legislative Studies
    • /
    • v.26 no.2
    • /
    • pp.113-140
    • /
    • 2020
  • This study is meaningful in that it is the first analysis of Korean elections using the concept of spatial autocorrelation. Spatial autocorrelation means that an event occurring in one location in space has a high correlation with an event occurring in the surrounding area. The voter turnout rate in the 21st general election of Seoul area was divided into the early-voting turnout and voting-day turnout, and the spatial pattern of the turnout was examined. Most of the previous studies were based on the unit of the precinct and personal data, but this study analyzed on the basis of the lower unit, Eup-myeon-dong, and analyzed using spatial data and aggregate data. Moran I index showed a fairly high spatial autocorrelation of 0.261 in the voting-day turnout, while the index of the early-voting turnout was low at 0.095, indicating that there was little spatial autocorrelation despite statistical significance. The voting-day turnout, which showed strong spatial autocorrelation, was compared and analyzed using the OLS regression model and the spatial statistics model. In the general regression model, the coefficient of determination R2 rose from 0.585261 to 0.656631 in the spatial error model, showing an increase in explanatory power of about 7 percentage points. This means that the spatial statistical model has high explanatory power. The most interesting result is the relationship between the early-voting turnout and the voting-day turnout. The higher the early-voting turnout is, the lower the voting-day turnout is. When the early-voing turnout increases by about 2%, the voting-day turnout drops by about 1%. In this study, the variables affecting the early-voting turnout and the voting-day turnout are very different. This finding is different from the previous researches.

Concurrent Validity of the Self-Report and Proxy-Report Versions of a Health-Related Quality of Life Measure: A Focus Group Study (초등학교 아동과 보호자에게 적용한 삶의 질 평가도구의 동시타당도 연구: 표적집단 파일럿연구)

  • Choi, Bongsam
    • The Journal of Korean Academy of Sensory Integration
    • /
    • v.21 no.2
    • /
    • pp.45-57
    • /
    • 2023
  • Objective : The purpose of this study was to investigate the concurrent validity of the self- and proxy-report versions of the KIDSCREEN-10 quality of life questionnaire. Methods : A total of nine children and nine parents were selected to represent a cohort registered for a school-based wellness program. Two versions of the KIDSCREEN-10 questionnaire (self- and proxy reports) were administered to the children and their parents. The Rasch rating scale model was applied to determine the dimensionality and item difficulty of the two versions of the questionnaire. Moreover, the item-person matching map and Spearman's rho were compared to confirm the concurrent validity of the two versions. Results : All items, except four items (i.e., autonomy, home life, concentration/learning, and peers/social support), fit the Rasch rating scale model of the children's self-report version of the questionnaire. With regard to the parent's proxy-report version, two items misfit the model. While the items of the self- and proxy-report versions showed similar item difficulties, the parents had a tendency to be more severe in their ratings than the children. The correlation between the two versions was relatively low (Spearman's rho = .533, p > .05). The scatterplots between the two versions showed differences in the item difficulties of the physical and psychological well-being and self-perception items. Conclusion : These findings suggest that the three identified items should be taken into consideration when measuring children's health-related quality of life using the KIDSCREEN-10 questionnaire.

Characterization of the Behavior of Naturally Occurring Radioactive Elements in the Groundwater within the Chiaksan Gneiss Complex : Focusing on the Mineralogical Interpretation of Artificial Weathering Experiments (치악산 편마암 지질의 지하수 내 자연 방사성 원소의 거동 특성 연구: 인공풍화 실험을 통한 광물학적 해석)

  • Woo-Chun Lee;Sang-Woo Lee;Hyeong-Gyu Kim;Do-Hwan Jeong;Moon-Su Kim;Hyun-Koo Kim;Soon-Oh Kim
    • Korean Journal of Mineralogy and Petrology
    • /
    • v.36 no.4
    • /
    • pp.289-302
    • /
    • 2023
  • The study area was Gangnim-myeon, Hoengseong-gun, Gangwon-do, composed of the Chiaksan gneiss complex, and it was revealed that the concentrations of uranium (U) and thorium (Th) within the groundwater of the study area exceeded their water quality standards. Hence, artificial weathering experiments were conducted to elucidate mineralogically the mechanisms of their leaching using drilling cores obtained from the corresponding groundwater aquifers. First of all, the mineralogical compositions of core samples were observed, and the results indicated that the content of clinochlore, a member of the chlorite group of minerals that can form through low- and intermediate-temperature metamorphisms, was relatively higher. In addition, the Th concentration was measured ten times higher than that of U. The results of artificial weathering experiments suggested that the Th concentrations gradually increased through the dissolution of radioactive-element-bearing minerals up to the first day, and then they tended to decrease. It could be attributed to the fact that Th was leached with the dissolution of thorite, which might be a secondary mineral, and then dissolved Th was re-precipitated as the various forms of salt, such as sulfate. Even though the U content was lower than that of Th in the core samples, the U concentration was one hundred times higher than that of Th after the weathering experiments. It is likely caused by the gradual dissolution and desorption of U included in intensively weathered thorite or adsorbed as a form of UO22+ on the mineral surface. In addition, the leaching tendency of U and Th was positively correlated with the bicarbonate concentration. However, the concentrations between U and Th in groundwater exhibited a relatively lower correlation, which might result from the fact that they occurred from different sources, as aforementioned. Among various kinetic models, the parabolic diffusion and pseudo-second-order kinetic models were confirmed to best fit the dissolution kinetics of both elements. The period that would be taken for the U concentration to exceed its drinking-water standard was inferred using the regressed parameters of the best-fitted models, and the duration of 29.4 years was predicted in the neutral-pH aquifers with relatively higher concentrations of HCO3, indicating that U could be relatively quickly leached out into groundwater.

Study on data preprocessing methods for considering snow accumulation and snow melt in dam inflow prediction using machine learning & deep learning models (머신러닝&딥러닝 모델을 활용한 댐 일유입량 예측시 융적설을 고려하기 위한 데이터 전처리에 대한 방법 연구)

  • Jo, Youngsik;Jung, Kwansue
    • Journal of Korea Water Resources Association
    • /
    • v.57 no.1
    • /
    • pp.35-44
    • /
    • 2024
  • Research in dam inflow prediction has actively explored the utilization of data-driven machine learning and deep learning (ML&DL) tools across diverse domains. Enhancing not just the inherent model performance but also accounting for model characteristics and preprocessing data are crucial elements for precise dam inflow prediction. Particularly, existing rainfall data, derived from snowfall amounts through heating facilities, introduces distortions in the correlation between snow accumulation and rainfall, especially in dam basins influenced by snow accumulation, such as Soyang Dam. This study focuses on the preprocessing of rainfall data essential for the application of ML&DL models in predicting dam inflow in basins affected by snow accumulation. This is vital to address phenomena like reduced outflow during winter due to low snowfall and increased outflow during spring despite minimal or no rain, both of which are physical occurrences. Three machine learning models (SVM, RF, LGBM) and two deep learning models (LSTM, TCN) were built by combining rainfall and inflow series. With optimal hyperparameter tuning, the appropriate model was selected, resulting in a high level of predictive performance with NSE ranging from 0.842 to 0.894. Moreover, to generate rainfall correction data considering snow accumulation, a simulated snow accumulation algorithm was developed. Applying this correction to machine learning and deep learning models yielded NSE values ranging from 0.841 to 0.896, indicating a similarly high level of predictive performance compared to the pre-snow accumulation application. Notably, during the snow accumulation period, adjusting rainfall during the training phase was observed to lead to a more accurate simulation of observed inflow when predicted. This underscores the importance of thoughtful data preprocessing, taking into account physical factors such as snowfall and snowmelt, in constructing data models.