• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.183-183
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• 2017

In the early part of rice growth, root volume primarily limits the amount of plant-accessible nitrogen (N). Therefore, knowledge of the root development is important for modeling N uptake of rice. The timing when the volume of rhizosphere cover the whole soil is also important to carry out timely top dressing. However, information about initial root expansion and associated N uptake is limited due to intrinsic technical difficulties in assessing below-ground processes. Some studies, however, showed a close relationship between below-ground root and above-ground leaf development, suggesting a possibility that above-ground attributes could serve as surrogates for the root processes. In this study, we investigated the relationship between below-ground and above-ground development of rice. Field experiments were conducted where we cultivated Koshihikari (a leading cultivar in Japan) for four different cropping schedules in 2012. In 2016, Gimbozu (HEG4) and three flowering time mutant lines of Gimbozu (X61 (se13), HS276 (ef7), DMG9 (se13, ef7)) were examined for a single season. Experiments were performed with three replications in a completely randomized design. We monitored ammonium-N concentration ([NH4+-N]) in soil solution by repeatedly taking samples from a porous tubing (10-cm long) vertically inserted at the most distant point from surrounding rice hills. Samples were taken in triplicate (= triplicate tubes) and every three days from transplanting in each experimental unit. For above-ground attributes, leaf area index (LAI) was measured in 2012, whereas soil coverage ratio was estimated by image processing in 2016. Results showed that [NH4+-N] increased gradually after transplanting and then rapidly decreased from a certain day. This distinct drop in [NH4+-N] informed us the timing at which the rice root system reached the point of porous tubing and thus essentially covered the whole soil volume. The LAI at the dropping point was about 0.43 regardless of the cropping schedules in 2012 experiment. In 2016, the coverage ratio at the N dropping point was within the range of 0.12 to 0.19 for four genotypes having different growth durations. In addition, the coverage ratios at seven weeks after the transplanting showed a good correspondence to LAI across the four genotypes. We therefore conclude that both LAI and coverage ratio may serve as robust indicators for root development and might be useful to estimate the timing when the root system fully cover the soil volume. Results obtained here will also contribute to develop models that can predict not only above-ground canopy development but also associated below-ground processes.

• Journal of Korean Society of Forest Science
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• v.97 no.1
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• pp.22-29
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• 2008

The objective of this study is to provide useful information for the establishment of efficient policy implementation strategies of forest road construction policy in South Korea. Data needed for the analysis was collected by a questionnaire survey. For the analysis, policy evaluation model was constructed based on theories of public policy. Evaluation model contains three independent variables (policy initiative factor, policy content, policy environment) and two dependent variables (policy result, policy impact). Since, these variables are unobservable latent variables, observable indicators are needed as proxy measures. LISREL (Linear Structural Relationships) was employed for the analysis since it is a useful measure for analysing linear structural model which consists of structural and measurement equations. It was confirmed that forest road construction is an effective policy mean for the development of rural region and activating forest resources management. The policy outcome, however, was not satisfactory. To improve the effectiveness of forest road construction policy some modification of policy contents are needed such as increased construction budget, allowing more flexibility and participation to the implementation personal and providing technical support.

• Management & Information Systems Review
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• v.33 no.1
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• pp.45-63
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• 2014

A trading system is a computer trading program that automatically submits trades to an exchange. Mechanical a trading system to execute trade is spreading in the stock market. However, a trading system to trade a single asset might occur instability of the profit because payoff of this system is determined a asset movement. Therefore, it is necessary to develop a trading system that is trade two assets such as a pair trading that is to sell overvalued assets and buy the undervalued ones. The aim of this study is to propose a relative value based trading system designed to yield stable and profitable profits regardless of market conditions. In fact, we propose a procedure for building a trading system that is based on the rough set analysis of indicators derived from a price ratio between two assets. KOSPI 200 index futures and S&P 500 index futures are used as a data for evaluation of the proposed trading system. We intend to examine the usefulness of this model through an empirical study.

• The Journal of the Petrological Society of Korea
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• v.24 no.3
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• pp.193-207
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• 2015

This study analyzed ancient documents and established petrological database through extensive field investigation of provenance sites to presume stone source areas of the Seoul City Wall. By summarizing the ancient documents, the rampart stone was mostly supplied from a stony mountain adjacent to the City Wall in the early Joseon period, whereas the stone was provided from fixed quarry outside the City Wall in the late Joseon period. As a result of the petrological investigation based on quarries recorded in the ancient documents, pinkish granite and leucogranite were distributed as a whole, and the granitoid rocks are similar in mineralogical compositions and geochemical behavior characteristics. However, the pinkish granite with magnetic-series show that the magnetic susceptibility increased from the north slope of Namsan Mountain to Bulamsan Mountain. The leucogranite with ilmenite-series mainly occurred along the boundary between granite and gneiss from Yongmasan Mountain to Inwangsan Mountain. Consequently, the important petrological indicators for presumption of stone source areas are the rock color and the magnetic susceptibility. In addition to the petrological features, the reliability for provenance interpretation should improve considering stone quantities in the quarries, transportation distance and technical skills.

• Journal of the Korea Institute of Building Construction
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• v.20 no.1
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• pp.83-91
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• 2020

The recent bridge construction projects is demanded more sophisticated risk management measures and loss forecasts to brace for risk losses from an increase in the trend of bridge construction. This study aims to analyze the risk factors that caused the loss of material in actual bridge construction and to develop a quantified predictive loss model, based on the past record of insurance payment by major domestic insurance companies for bridge construction projects. For the development of quantitative bridge construction loss model, the dependent variable was selected as the loss ratio, i.e., the ratio of insurance payout divided by the total project cost, while the independent variable adopted 1) Technical factors: superstructure type, foundation type, construction method, and bridge length 2) Natural hazards: typhoon and flood 3) Project information: construction period and total project cost. Among the selected independent variables, superstructure type, construction method, and project period were shown to affect the ratio of bridge construction losses. The results of this study can provide government agencies, bridge construction design and construction and insurance companies with the quantitative damage prediction and risk assessment services, using risk indicators and loss prediction functions derived from the findings of this study and can be used as a guideline for future basic bridge risk assessment development research.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2016.05a
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• pp.404-430
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• 2016

This study started from the awareness of the issue if the citation index newly introduced to evaluate the quality of papers satisfies the proper timing matter, which is a component of performance indicators for the evaluation of government-funded R&D institutes. Accordingly, the study will propose improvement ways to shift the previous evaluation system to quality evaluation for mission-oriented R&D institutes by analysing and using the periodical characteristics such as citation half-life and immediacy index of papers. As a result, it turned out that the speed of academic change is getting faster in proportion to the dependency on the technological development but that the citation speed in the field of public technology is relatively slower and the speed of knowledge transfer in the fields related to industry is faster. In addition, the citation index among the R&D fields showed no differences, and the minimum period for citation index measurement with validity should be over 6 years. The problems of evaluation for mission-oriented R&D institutes were deducted based on the technical and statistical analysis results of the temporal characteristic of citation necessary for quality evaluation of performance among R&D fields. To solve the problems, policy alternatives for object and valid quality evaluation were proposed from the points of evaluation period, evaluation criteria, and evaluation management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.190-199
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• 2019

This study was conducted to expand the distribution of new technology efficiently by analyzing the structure relationship based on the innovation resistance model and partial least square structural equation model (PLS-SEM). This study selected innovative propensity, relative advantage, compatibility, complexity, trialability, risk, and extension service consisting of educational, technical, and funding services as factors affecting innovation resistance. This study constructed a questionnaire that measured 11 factors including acceptance intention of new technology using 33 indicators. Data was from April to October, 2017, targeting 180 farmers who did not join in projects to spread new technologies of the Rural Development Administration. Results showed the factors positively and significantly affecting innovation resistance include complexity and risk. Innovative propensity did not have any effect on innovation resistance. However, it positively affected acceptance intention of new technology. The service of the extension organizations had a negative effect on innovation resistance, but did not affect acceptance intention of new technology. This study suggests that extension services should promote activities such as education, consulting, publicity and pilot projects related with new technologies in order to minimize the antipathy toward new agricultural technologies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.25-40
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• 2019

Many companies are executing big data analysis and utilization projects to legitimize the development of new business areas or conversion of management or technical strategies. In Korea and abroad, however, such projects are failing because they are not completed within specified deadlines, which is not unrelated to the current situation in which the knowledge base for big data project risk management from an engineering perspective is grossly lacking. As such, the current study analyzes the risk factors of big data implementation and utilization projects, in addition to finding risk factors that are highly important. To achieve this end, the study extracts project risk factors via literature review, after which they are grouped using affinity methodology and sifted through expert surveys. The deduced risk factors are structuralize using factor analysis to develop a table that categorizes various types of big data project risk factors. The current study is significant that in it provides a basis for developing basic control indicators related to risk identification, risk assessment, and risk analysis. The findings from the study contribute greatly to the success of big data projects, by providing theoretical basis regarding efficient big data project risk management.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.745-760
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• 2021

Prediction of a stock price has been a subject of interest for a long time in financial markets, and thus, many studies have been conducted in various directions. As the efficient market hypothesis introduced in the 1970s acquired supports, it came to be the majority opinion that it was impossible to predict stock prices. However, recent advances in predictive models have led to new attempts to predict the future prices. Here, we summarize past studies on the price prediction by evaluation measures, and predict the direction of stock prices of Samsung Electronics, LG Chem, and NAVER by applying various machine learning models. In addition to widely used technical indicator variables, accounting indicators such as Price Earning Ratio and Price Book-value Ratio and outputs of the hidden Markov Model are used as predictors. From the results of our analysis, we conclude that no models show significantly better accuracy and it is not possible to predict the direction of stock prices with models used. Considering that the models with extra predictors show relatively high test accuracy, we may expect the possibility of a meaningful improvement in prediction accuracy if proper variables that reflect the opinions and sentiments of investors would be utilized.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.245-256
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• 2021

The Fourth Industrial Revolution brought the quantitative value of data across the industry and entered the era of 'Big Data'. This is due to both the rapid development of information & communication technology and the diversity & complexity of customer purchasing tendencies. An enterprise's core competence in the Big Data Era is to analyze and utilize the data to make strategic decisions for enterprise. However, most of traditional studies on Big Data have focused on technical issues and future potential values. In addition, these studies lacked interest in managing the quality and utilization levels of internal & external customer Big Data held by the entity. To overcome these shortages, this study attempted to derive influential factors by recognizing the quality management information systems and quality management of the internal & external Big Data. First of all, we conducted a survey of 204 executives & employees to determine whether Big Data quality management, Big Data utilization, and level management have a significant impact on corporate work efficiency & corporate management performance. For the study for this purpose, hypotheses were established, and their verifications were carried out. As a result of these studies, we found that the reasons that significantly affect corporate management performance are support from the management class, individual innovation, changes in the management environment, Big Data quality utilization metrics, and Big Data governance system.