The performance of the newly designed Pusan National University Coupled General Circulation Model (PNU CGCM) Ensemble Forecast System which produce 40 ensemble members for 12-month lead prediction is evaluated and analyzed in terms of boreal winter temperature over South Korea (S. Korea). The influence of ensemble size on prediction skill is examined with 40 ensemble members and the result shows that spreads of predictability are larger when the size of ensemble member is smaller. Moreover, it is suggested that more than 20 ensemble members are required for better prediction of statistically significant inter-annual variability of wintertime temperature over S. Korea. As for the ensemble average (ENS), it shows superior forecast skill compared to each ensemble member and has significant temporal correlation with Automated Surface Observing System (ASOS) temperature at 99% confidence level. In addition to forecast skill for inter-annual variability of wintertime temperature over S. Korea, winter climatology around East Asia and synoptic characteristics of warm (above normal) and cold (below normal) winters are reasonably captured by PNU CGCM. For the categorical forecast with $3{\times}3$ contingency table, the deterministic forecast generally shows better performance than probabilistic forecast except for warm winter (hit rate of probabilistic forecast: 71%). It is also found that, in case of concentrated distribution of 40 ensemble members to one category out of the three, the probabilistic forecast tends to have relatively high predictability. Meanwhile, in the case when the ensemble members distribute evenly throughout the categories, the predictability becomes lower in the probabilistic forecast.
The purpose of this study focuses on and explain the policy-determining factors that emerged in the process of revising customized wages for the National Basic Livelihood Security Act on December 30, 2014. This is an analysis of the reasons why the rapid revision of the welfare system could have been made at a certain time in a situation that did not progress despite the specific demand for revision of the law surrounding the blind spot. To this end, using Kingdon's policy flow model, which emphasizes the contingency of policy decisions, the flow of problems, political flows, and policy alternatives were reviewed respectively. In the course of each of these flows, the suicide incident of mother and 2 daughters in Songpa served as a major medium that played a large role in the policy-making process and the window of policy could be opened. As a result, This incident triggered social and policy interest in the issue of the National Basic Livelihood Security Act. It was found that the law was revised quickly, causing a great wave of waves as a social issue.
Journal of Korea Society of Industrial Information Systems
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v.14
no.5
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pp.239-256
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2009
The major issues of managing an organization and its environments are on how to establish a community for their co-survival and collaboration. This study is on the principles and management practices for establishing the community of organization and its environments based on the power circulatory approach, so that it contributes to creation of the social orders for co-survival and collaboration. In order to do this I discussed the theories and practices of the power circulatory approach, and then suggest their application to establishment of the co-survival community for organization and its environment. According to results the power circulatory approach offers theoretical and managerial tools which establish the co-survival community for organization and its environments, so that it increases likelihood of their co-survival and collaboration. Furthermore I discussed the position of the power circulatory approach to co-survival and collaboration in a manner that displays similarities and differences with exiting approaches such as the contingency and population ecology model.
Journal of Korean Society of Industrial and Systems Engineering
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v.40
no.4
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pp.78-86
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2017
The new businesses started by the companies usually results in being unsuccessful. The main reasons for that are either aiming targeting wrong customers, unsatisfaction of customers' requesting quality standards, or taking wrong actions against the competitors in the market. Therefore, companies should aim the targets for the newly developing products based on the fulfilling values for the customers when they start the new businesses, and should take good cares for risk managements at the each step of the new business to prevent the failure in advance. In addition to that, the companies starting new businesses not only need to take the customers attributes (CA) into account, but they also should apply the new technologies as one system to initiate a new business to satisfy the basic wants of the customers. This article suggests the New Product Development Pursuing Model using the Indicative Planning methodology and the Quality Management tools. The New Product Development Pursuing Model would be completed by the following steps as below; 1. Drawing the CTQ (Critical To Quality) for setting up the new product development objectives by : i) using the VOC (Voice Of Customers) obtained by the QFD (Quality Function Deploypment) if the market is mature, ii) applying AHP (Analytic Hierarchy Process) to information in the QIS (Quality Information System) if the market is unmature to get enough need information of the customers. 2. Risk Management in NPD : The NPD pursuing model consisted of the IP (indicative planning) is suggested not by the process of top-down-way mandatory planning process, but by the tools used in the administrative science and economic fields, namely by governance. The companies could apply innovative methodology for new products development processes to fulfil the customers satisfaction in the fields, through the CA (Contingency Approach) of the NPD (New Product Development) process.
The purpose of this study is to develop the ITS evaluation model using the Probabilistic Risk Analysis (PRA) methodology and to demonstrate the goodness-of-fit of the large ITS projects through the comparative analysis between DEA and PRA model. The results of this study are summarized below. First, the evaluation mode] using PRA with Monte-Carlo Simulation(MCS) and Latin-Hypercube Sampling(LHS) is developed and applied to one of ITS projects initiated by local government. The risk factors are categorized with cost, benefit and social-economic factors. Then, PDF(Probability Density Function) parameters of these factors are estimated. The log-normal distribution, beta distribution and triangular distribution are well fitted with the market and delivered price. The triangular and uniform distributions are valid in benefit data from the simulation analysis based on the several deployment scenarios. Second, the decision making rules for the risk analysis of projects for cost and economic feasibility study are suggested. The developed PRA model is applied for the Daejeon metropolitan ITS model deployment project to validate the model. The results of cost analysis shows that Deterministic Project Cost(DPC), Deterministic Total Project Cost(DTPC) is the biased percentile values of CDF produced by PRA model and this project need Contingency Budget(CB) because these values are turned out to be less than Target Value(TV;85% value), Also, this project has high risk of DTPC and DPC because the coefficient of variation(C.V) of DTPC and DPC are 4 and 15 which are less than that of DTPC(19-28) and DPC(22-107) in construction and transportation projects. The results of economic analysis shows that total system and subsystem of this project is in type II, which means the project is economically feasible with high risk. Third, the goodness-of-fit of PRA model is verified by comparing the differences of the results between PRA and DEA model. The difference of evaluation indices is up to 68% in maximum. Because of this, the deployment priority of ITS subsystems are changed in each mode1. In results. ITS evaluation model using PRA considering the project risk with the probability distribution is superior to DEA. It makes proper decision making and the risk factors estimated by PRA model can be controlled by risk management program suggested in this paper. Further research not only to build the database of deployment data but also to develop the methodologies estimating the ITS effects with PRA model is needed to broaden the usage of PRA model for the evaluation of ITS projects.
The prediction model is the main factor affecting the performance of a knowledge-based system for bankruptcy prediction. Earlier studies on prediction modeling have focused on the building of a single best model using statistical and artificial intelligence techniques. However, since the mid-1980s, integration of multiple techniques (hybrid techniques) and, by extension, combinations of the outputs of several models (ensemble techniques) have, according to the experimental results, generally outperformed individual models. An ensemble is a technique that constructs a set of multiple models, combines their outputs, and produces one final prediction. The way in which the outputs of ensemble members are combined is one of the important issues affecting prediction accuracy. A variety of combination schemes have been proposed in order to improve prediction performance in ensembles. Each combination scheme has advantages and limitations, and can be influenced by domain and circumstance. Accordingly, decisions on the most appropriate combination scheme in a given domain and contingency are very difficult. This paper proposes a confidence-based selection approach as part of an ensemble bankruptcy-prediction scheme that can measure unified confidence, even if ensemble members produce different types of continuous-valued outputs. The present experimental results show that when varying the number of models to combine, according to the creation type of ensemble members, the proposed combination method offers the best performance in the ensemble having the largest number of models, even when compared with the methods most often employed in bankruptcy prediction.
Jo, Sera;Lee, Joonlee;Shim, Kyo Moon;Kim, Yong Seok;Hur, Jina;Kang, Mingu;Choi, Won Jun
Korean Journal of Agricultural and Forest Meteorology
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v.23
no.4
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pp.391-404
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2021
This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.
Korean Journal of Agricultural and Forest Meteorology
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v.18
no.4
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pp.307-319
/
2016
A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.
The importance of technological innovation orientation, which denotes the firm's general direction of thought toward steadily pursuing and promoting technological innovation in the long run for its viability and competitiveness, is on the rise. Although the technological innovation orientation has conceptually and practically important implications for securing the firm's sustainable competitive advantage, to date there has been limited research systematically analyzing the role of the technological innovation orientation for the firm's successful technological innovation and performance. Recognizing such deficiency in previous research regarding technological innovation orientation, this study selected internal and external critical factors which might affect the technological innovation orientation, and proposed and empirically examined a research model and hypotheses demonstrating the contingency relationships among the antecedent factors, technological innovation orientation and technological innovation performance. In the proposed research model, the selected antecedents of technological innovation orientation included two internal factors of CEO's technical-function experience and cross-functional integration and two external factors of environmental uncertainty and intensity of competition, and eventually it was suggested that these antecedent factors affected the firm's technological innovation performance via the technological innovation orientation. In addition, the research model suggested that the two environmental factors of environmental uncertainty and intensity of competition had a positive moderation effect on the relationship between technological innovation orientation and technological innovation performance. Analysis of data on sample of 86 Korean IT SMEs showed that CEO's technical-function experience, cross-functional integration and environmental uncertainty had a positive impact on the firm's technological innovation orientation and that the technological innovation orientation positively influenced the firm's technological innovation performance. The results also revealed that environmental uncertainty positively moderated the relationship between the firm's technological innovation orientation and technological innovation performance. The theoretical and practical implications for the results of this study were discussed.
Journal of agricultural medicine and community health
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v.26
no.2
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pp.111-132
/
2001
This study was conducted to examine the therapeutic compliance and its related factors in rural women with osteoporosis. A questionnaire survey was performed from April to May in 2000 for 140 osteoporotic patients who were diagnosed from April to June in 1999 through community health program. The study employed the health belief model for predicting and explaining sick role behavior. The analysis techniques employed included contingency table analysis and path analysis using LISREL. The major results of this study were as follows: Of the subjects, 12.1% were continuously complaint, 53.6% were intermittently compliant, and 34.3% were non- compliant to calcium supplement therapy. As the result of path analysis, the therapeutic compliance was significantly higher(${\mid}T{\mid}$ >2.0) as patients had higher perceived severity of disease, lower perceived barriers of treatment, and when patients thought their disease status as severe. As the patients had higher educational level, more experience of mass media contact or health education about osteoporosis, and when family had more concern for patient treatment, they had higher perceived susceptibility of complication(bone fracture)${\mid}T{\mid}$ >2.0). The patients had higher perceived severity(${\mid}T{\mid}$ >2.0) as they had more educational level, more advice for treatment from their doctors, and when family had more concern for their treatment. As the patients had more advice for treatment from their doctors and when family had more concern for their treatment, they had higher perceived benefit of treatment and lower perceived barriers to treatment(${\mid}T{\mid}$ >2.0). In order to improve the therapeutic compliance in rural osteoporotic women, it would be necessary that the patient should recognize their disease severity properly. And the perceived barriers should be removed through supportive environments for osteoporosis treatment such as doctor 's more advice and family 's more concern for treatment. In addition, effective and continuous management system for osteoporotic patients should be established.
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