• Title/Summary/Keyword: 결정성 검증

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Control of Mg and P Ion Concentration as a Precondition to Use N, K and Ca Ion Sensors in Closed Hydroponics (N, K, Ca의 한정된 이온센서 이용을 전제로 한 순환식 수경재배에서 P, Mg의 조절 방법)

  • Choi, Gyeong Lee;Yeo, Kyung Hwan;Rhee, Han Cheol;Lee, Seong Chan;Lee, Jung-Sup;Kang, Nam Jun;Kim, Hak Jin;Jung, Dae Hyun
    • Horticultural Science & Technology
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    • v.34 no.6
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    • pp.871-877
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    • 2016
  • Recycling nutrient solutions in closed hydroponic production systems is usually accompanied by an imbalance of nutrient solutions when concentration is controlled according to electrical conductivity (EC) levels. This study investigated whether it was possible to automatically control the concentrations of five essential elements nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg) using only N, K and Ca ion sensors. N, P, K, Ca, and Mg uptake was measured in the nutrient solution, and relationships between absorbed ions were analyzed through twice-repeated experiments in lettuce. Results confirmed that the pattern of $PO_4$ ion uptake was similar that of N, and the pattern of Mg ion uptake was similar that of Ca. $PO_4$ ion uptake was most highly correlated with N, and Mg was most highly correlated with Ca. Regression coefficients of N and $PO_4$ were significantly different at 1.04 and 0.55, respectively, but were similar between Ca and Mg at 0.35 and 0.40, respectively. Additional experiments were conducted to measure nutrient uptake in pak choi and rose plants, both to confirm the results from the first experiment in lettuce, and to assess possible application to other crops. Coefficients of determination both for N and $PO_4$, and Ca and Mg were considerably high ($R^2=0.86$) in cultured pak choi, and similar results were observed in cultured rose ($R^2=0.87$ and 0.73, respectively). Regression coefficients for cultured pak choi were 0.56 and 0.24, respectively, and for rose were 0.51 and 0.16, respectively. Although the results obtained for N and $PO_4$ were not consistent between the lettuce experiments, N and $PO_4$ have similar regression coefficients for all crops. No common coefficient was found between Ca and Mg.

Assessment Research Comparing the Environmental Value of Taebaeksan·NakSan·Kyeongpo Provincial Parks of Kangwon-do (태백산, 낙산, 경포도립공원의 환경가치비교 평가연구)

  • Kang, Kee-Rae;Kim, Dong-Pil;Cho, Woo;Baek, Jae-Bong
    • Korean Journal of Environment and Ecology
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    • v.30 no.2
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    • pp.253-260
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    • 2016
  • This research aimed to quantitatively measure the environmental values of Taebaeksan, Naksan, and Gyeongpo provincial parks located in Gangwon-do. The research was based on the CVM technique which estimates the economic values for all kinds of ecosystem. Also, the estimated value of environment goods can suggest the magnitude of additional utility other than the cost people pay when they visit the provincial parks. Such result can be used as basic data in addition to information on natural ecology or cultural landscape to decide whether the park should be promoted as a national park. The questionnaires-collected from Taebaeksan(180 copies), Naksan(179 copies), and Gyeongpo(180 copies) provincial parks were used to measure the environmental value of each provincial park. Variables that affect the response of 'yes(Y)' or 'no(N)' to the cost suggestion for the economic valuation of environment are estimated under the catagories of environment conservation status (env.), degree of park management (manage.), environmental conservation effort, education (edu.), and income (inc.) of the respondents (execu.), pertaining to the 3 provincial parks in Gangwon-do. The value of natural environment to 1 visitor to the 3 Gangwon provincial parks was estimated by the Logit method that Hanemann proposed using the average of inserted variables. The results showed that the additional environmental value that 1 visitor can gain is 44,060 won for Taebaeksan Provincial Park, 41,191 won for Naksan, and 41,844 won for the Gyeongpo Provincial Park. Taebaeksan Provincial Park's environmental value is estimated at the highest as the respondents judge that its natural environment is well preserved and the facilities are managed well.

Simulation Conditions based Characteristics of Spatial Flood Data Extension (모의조건에 따른 홍수 유출자료의 공간적 확장 영향분석)

  • Kim, Nam Won;Jung, Yong;Lee, Jeong Eun
    • Journal of Korea Water Resources Association
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    • v.47 no.6
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    • pp.501-511
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    • 2014
  • The effects of initial conditions and input values of the rainfall-runoff model were studied in the applications of a lumped concept model for flood event data extension. For the initial conditions of the rainfall-runoff model, baseflow effects and spatial distributions of saturation points ($R_{sa}$) for the storage function methods (SFM) were analyzed. In addition, researches on the effects of rainfall data conditions as input values for the rainfall-runoff model were performed. The Chungju Dam watershed was selected and divided into 3 catchments including smaller size of 22 sub-catchments. The observed discharge and inflow amounts at Yeongwol 1, Chungju Dam, and Yeongwol 2 water level stations were individually operated as criteria for flood data extension in 30 flood events from 1993 to 2009. Direct and base flow were distinguished from a stream flow. In order to test capability of flood data extension, obtained base flow was applied to the rainfall-runoff model for three water level stations. When base flow was adopted in the model, the Nash-Sutcliffe Efficiency(NSE) was increased. The numbers of over satisfaction for model performance (>0.5) were increased over 10%. Saturation points ($R_{sa}$) which strongly influence the runoff amount when rainfall starts were optimized based on the runoff amount at three water level stations. The sizes of saturation points for three locations were similar which means saturation point size is not depending on the runoff amount. The effects of rainfall information for flood runoff were tested at 2002ev1 and 2008ev1. When increased the amount of rainfall information, the runoff simulations were closer to the simulations with full of rainfall information. However, the size of improvement was not substantial on rainfall-runoff simulations in terms of the size of total amount of rainfall.

The Performance Formation Model of Service Quality Factors for Courier Service (택배산업의 서비스품질 성과형성 모델)

  • Song, Jang-Gwen;Kim, Tae-Ryong
    • Journal of Distribution Science
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    • v.10 no.4
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    • pp.37-45
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    • 2012
  • The popularity of courier services in Korea has made it an essential part of the country's domestic logistics industry, bolstering the growth not only of the national economy, but also the quality of people's daily lives. An effective strategy for courier companies in Korea would be to provide high-quality services to their existing target markets with the goal of maximizing customer loyalty. This study investigates structural relationships between customer loyalty and service quality as a set of factors and between customer trust and customer satisfaction. These antecedent relationships will be used to understand the "performance formation model" through service quality. In this study, service quality, as a set of factors, is considered to be the independent variable, while customer satisfaction and customer trust are both treated as intervening variables. Finally, customer loyalty is the dependent variable. Following a review of the literature, this paper's proffered hypothesis will be investigated in terms of whether the independent and intervening variables significantly affect customer loyalty. A statistical analysis of the empirical research was carried out using both SPSS 18.0 and AMOS 18.0 The results of this study's empirical analysis show three conclusions. First, among the intervening variables (customer satisfaction and customer trust), customer satisfaction is significantly correlated with customer loyalty. Customer trust, however, was shown to have little or no relationship to customer loyalty. Second, the quality of service variable seems to influence customer satisfaction, customer trust, and customer loyalty. Third, with respect to the relationship of intervening variables, customer trust affects customer satisfaction. Thus, the companies that have a competitive advantage in Korea have successfully maximized customer loyalty for their existing customers. Courier companies will need to research and study customer needs. Therefore, this research suggests that effective courier service management can be better understood through the application of the service quality performance formation model, which can enhance the quality of service provided by domestic courier services. This research is limited to investigating qualitative variables, such as the service quality factors, customer satisfaction, and customer trust. It would be helpful for future research on courier services to consider quantitative variables, such as price and weight.

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Least-Square Fitting of Intrinsic and Scattering Q Parameters (최소자승법(最小自乘法)에 의(衣)한 고유(固有) Q와 산란(散亂) Q의 측정(測定))

  • Kang, Ik Bum;McMechan, George A.;Min, Kyung Duck
    • Economic and Environmental Geology
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    • v.27 no.6
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    • pp.557-561
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    • 1994
  • Q estimates are made by direct measurements of energy loss per cycle from primary P and S waves, as a function of frequency. Assuming that intrinsic Q is frequency independent and scattering Q is frequency dependent over the frequencies of interest, the relative contributions of each, to a total observed Q, may be estimated. Test examples are produced by computing viscoelastic synthetic seismograms using a pseudo spectral solution with inclusion of relaxation mechanisms (for intrinsic Q) and a fractal distribution of scatterers (for scattering Q). The composite theory implies that when the total Q for S-waves is smaller than that for P-waves (the usual situation), intrinsic Q is dominating; when it is larger, scattering Q is dominating. In the inverse problem, performed by a global least squares search, intrinsic $Q_p$ and $Q_s$ estimates are reliable and unique when their absolute values are sufficiently low that their effects are measurable in the data. Large $Q_p$ and $Q_s$ have no measurable effect and hence are not resolvable. Standard deviation of velocity $({\sigma})$ and scatterer size (A) are less unique as they exhibit a tradeoff as predicted by Blair's equation. For the P-waves, intrinsic and scattering contributions are of approximately the same importance, for S-waves, the intrinsic contributions dominate.

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Spatial Downscaling of Ocean Colour-Climate Change Initiative (OC-CCI) Forel-Ule Index Using GOCI Satellite Image and Machine Learning Technique (GOCI 위성영상과 기계학습 기법을 이용한 Ocean Colour-Climate Change Initiative (OC-CCI) Forel-Ule Index의 공간 상세화)

  • Sung, Taejun;Kim, Young Jun;Choi, Hyunyoung;Im, Jungho
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.959-974
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    • 2021
  • Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R2)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R2=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.

Water shortage assessment by applying future climate change for boryeong dam using SWAT (SWAT을 이용한 기후변화에 따른 보령댐의 물부족 평가)

  • Kim, Won Jin;Jung, Chung Gil;Kim, Jin Uk;Kim, Seong Joon
    • Journal of Korea Water Resources Association
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    • v.51 no.12
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    • pp.1195-1205
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    • 2018
  • In the study, the water shortage of Boryeong Dam watershed ($163.6km^2$) was evaluated under future climate change scenario. The Soil and Water Assessment Tool (SWAT) was used considering future dam release derived from multiple linear regression (MLR) analysis. The SWAT was calibrated and verified by using daily observed dam inflow and storage for 12 years (2005 to 2016) with average Nash-Sutcliffe efficiency of 0.59 and 0.91 respectively. The monthly dam release by 12 years MLR showed coefficient of determination ($R^2$) of above 0.57. Among the 27 RCP 4.5 scenarios and 26 RCP 8.5 scenarios of GCM (General Circulation Model), the RCP 8.5 BCC-CSM1-1-M scenario was selected as future extreme drought scenario by analyzing SPI severity, duration, and the longest dry period. The scenario showed -23.6% change of yearly dam storage, and big changes of -34.0% and -24.1% for spring and winter dam storage during 2037~2047 period comparing with 2007~2016 period. Based on Runs theory of analyzing severity and magnitude, the future frequency of 5 to 10 years increased from 3 in 2007~2016 to 5 in 2037~2046 period. When considering the future shortened water shortage return period and the big decreases of winter and spring dam storage, a new dam operation rule from autumn is necessary for future possible water shortage condition.

Is Fertility Rate Proportional to the Quality of Life? An Exploratory Analysis of the Relationship between Better Life Index (BLI) and Fertility Rate in OECD Countries (출산율은 삶의 질과 비례하는가? OECD 국가의 삶의 질 요인과 출산율의 관계에 관한 추이분석)

  • Kim, KyungHee;Ryu, SeoungHo;Chung, HeeTae;Gim, HyeYeong;Park, HeongJoon
    • International Area Studies Review
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    • v.22 no.1
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    • pp.215-235
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    • 2018
  • Policy concerns related to raising fertility rates are not only common interests among the OECD countries, but they are also issues of great concern to South Korea whose fertility rate is the lowest in the world. The fertility rate in South Korea continues to decline, even though most of the national budget has been spent on measures to address this and many studies have been conducted on the increase in the fertility rates. In this regard, this study aims to verify the effectiveness of the detailed factors affecting the fertility rate that have been discussed in the previous studies on fertility rates, and to investigate the overall trend toward enhancing the quality of life and increasing the fertility rate through macroscopic and structural studies under the recognition of problems related to the policy approaches through the case studies of the European countries. Toward this end, this study investigated if a high quality of life in advanced countries contributes to the increase in the fertility rate, which country serves as a state model that has a high quality of life and a high fertility rate, and what kind of social and policy environment does the country have with regard to childbirth. The analysis of the OECD Better Life Index (BLI) and CIA fertility rate data showed that the countries whose people enjoy a high quality of life do not necessarily have high fertility rates. In addition, under the recognition that a country with a high quality of life and a high birth rate serves as a state model that South Korea should aim for, the social characteristics of Iceland, Ireland, and New Zealand, which turned out to have both a high quality of life and a high fertility rate, were compared with those of Germany, which showed a high quality of life but a low fertility rate. According to the comparison results, the three countries that were mentioned showed higher awareness of gender equality; therefore, the gender wage gap was small. It was also confirmed that the governments of these countries support various policies that promote both parents sharing the care of their children. In Germany, on the other hand, the gender wage gap was large and the fertility rate was low. In a related move, however, the German government has made active efforts to a paradigm shift toward gender equality. The fertility rate increases when the synergy lies in the relationship between parents and children; therefore, awareness about gender equality should be firmly established both at home and in the labor market. For this reason, the government is required to provide support for the childbirth and rearing environment through appropriate family policies, and exert greater efforts to enhance the effectiveness of the relevant systems rather than simply promoting a system construction. Furthermore, it is necessary to help people in making their own childbearing decisions during the process of creating a better society by changing the national goal from 'raising the fertility rate' to 'creating a healthy society made of happy families'

Estimation of irrigation return flow from paddy fields on agricultural watersheds (농업유역의 논 관개 회귀수량 추정)

  • Kim, Ha-Young;Nam, Won-Ho;Mun, Young-Sik;An, Hyun-Uk;Kim, Jonggun;Shin, Yongchul;Do, Jong-Won;Lee, Kwang-Ya
    • Journal of Korea Water Resources Association
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    • v.55 no.1
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    • pp.1-10
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    • 2022
  • Irrigation water supplied to the paddy field is consumed in the amount of evapotranspiration, underground infiltration, and natural and artificial drainage from the paddy field. Irrigation return flow is defined as the excess of irrigation water that is not consumed by evapotranspiration and crop, and which returns to an aquifer by infiltration or drainage. The research on estimating the return flow play an important part in water circulation management of agricultural watershed. However, the return flow rate calculations are needs because the result of calculating return flow is different depending on irrigation channel water loss, analysis methods, and local characteristics. In this study, the irrigation return flow rate of agricultural watershed was estimated using the monitoring and SWMM (Storm Water Management Model) modeling from 2017 to 2020 for the Heungeop reservoir located in Wonju, Gangwon-do. SWMM modeling was performed by weather data and observation data, water of supply and drainage were estimated as the result of SWMM model analysis. The applicability of the SWMM model was verified using RMSE and R-square values. The result of analysis from 2017 to 2020, the average annual quick return flow rate was 53.1%. Based on these results, the analysis of water circulation characteristics can perform, it can be provided as basic data for integrated water management.

The prediction of the stock price movement after IPO using machine learning and text analysis based on TF-IDF (증권신고서의 TF-IDF 텍스트 분석과 기계학습을 이용한 공모주의 상장 이후 주가 등락 예측)

  • Yang, Suyeon;Lee, Chaerok;Won, Jonggwan;Hong, Taeho
    • Journal of Intelligence and Information Systems
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    • v.28 no.2
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    • pp.237-262
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    • 2022
  • There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.