• Journal of Environmental Policy
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• v.14 no.3
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• pp.75-94
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• 2015

The purpose of this study is to analyze the major issues discussed among Parties and provide a framework for predicting the agreements on those issues, prior to the final negotiation on a new legally-binding agreement on climate change adaptation in the United Nations Framework Convention on Climate Change (UNFCCC). The analyses of documents, adaptation actions, and work of the Ad Hoc Working Group on the Durban Platform for Enhanced Action (ADP) under the UNFCCC informed that the adaptation issue has primarily been focused on the support of developed country Parties for the adaptation of developing country Parties following the principle of the Convention, Common but Differentiated Responsibilities and Respective Capabilities (CBDR-RC). Three-year work of the ADP acknowledged the major issues on adaptation in the new climate agreement, which would be categorized as long-term and global aspects, commitments/contributions/actions, monitoring and evaluation, institutional arrangements, and loss and damage. A final agreement on each issue could be predicted by setting a zone of possible agreement in-between the two extremes of developing and developed country Parties and considering three major elements affecting the Parties' positions, national priority, adaptation action, and social expectation, which are proposed in this study. The three major elements should be considered in a balanced manner by Parties to draw a durable agreement that will enhance global adaptation actions from a long-term perspective. That is, the agreement needs to reflect adaptation actions occurring outside the Convention as well as social expectations for adaptation. It is expected that the new agreement on climate change adaptation, from a long-term and global perspective, would be an opportunity to reduce vulnerability and build resilience to climate change by incorporating global expectations.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.94-108
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• 2021

This study is to identify the internal and external factors of a company that can affect the rate of change in the inventory turnover ratio. In addition, by appropriately managing or responding to these factors, changes in the inventory turnover ratio do not occur abruptly, so that the company's business and financial performance can be improved. To confirm this, factors such as gross profit margin, cash flow volatility, advertising expenses, inflation, exchange rate rise, and leading economic index were selected, and these factors were predicted to affect the change rate of inventory turnover. Data of 85,878 companies were obtained from domestic securities listings, KOSDAQ listings, and externally audited companies, and multiple regression analysis was performed using the data. Gross profit margin and cash flow volatility have a significant positive (+) effect, advertising expenses have a negative (-) significant effect, and inflation and exchange rate rises have a negative (-) significant effect. As an influence, the leading economic index was tested to have a significant positive (+) effect. Through this, it is suggested that manufacturing companies can improve their business performance and achieve operational efficiency by well understanding and appropriately managing factors that can affect the change rate of inventory turnover.

• Progress in Medical Physics
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• v.20 no.3
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• pp.132-138
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• 2009

Studies on target motion in 4-dimensional radiotherapy are being world-widely conducted to enhance treatment record and protection of normal organs. Prediction of tumor motion might be very useful and/or essential for especially free-breathing system during radiation delivery such as respiratory gating system and tumor tracking system. Neural network is powerful to express a time series with nonlinearity because its prediction algorithm is not governed by statistic formula but finds a rule of data expression. This study intended to assess applicability of neural network method to predict tumor motion in 4-dimensional radiotherapy. Scaled Conjugate Gradient algorithm was employed as a learning algorithm. Considering reparation data for 10 patients, prediction by the neural network algorithms was compared with the measurement by the real-time position management (RPM) system. The results showed that the neural network algorithm has the excellent accuracy of maximum absolute error smaller than 3 mm, except for the cases in which the maximum amplitude of respiration is over the range of respiration used in the learning process of neural network. It indicates the insufficient learning of the neural network for extrapolation. The problem could be solved by acquiring a full range of respiration before learning procedure. Further works are programmed to verify a feasibility of practical application for 4-dimensional treatment system, including prediction performance according to various system latency and irregular patterns of respiration.

• Korean Journal of Construction Engineering and Management
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• v.17 no.2
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• pp.21-30
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• 2016

The current PF project is entirely relying on construction company's credibility. As such, it has increased a negative and bad recognition in domestic real estate economy. In addition, PF experts has a perception that a project's safety of future cash flow profitability is more important than the construction company's credibility. So many PF experts make an effort in order to set aside safe project structure of PF and analyse systematically the risks of the project. In common feasibility study of the PF Project, financial specialists and real estate specialists are forecasting and evaluating the suitability of the project through reviewing the development profit from the project of sales. However, cash flow analysis and evaluation from the perspective of mid-sized construction companies are still in the primary level. Therefore, this study has analysed the current feasibility study and go/no go decision making procedures. Then the authors have a new cash flow analysis method from the perspective of mid-sized construction companies, by improving the feasibility study and go/no go decision making procedures.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.67-83
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• 2018

The Korean film industry with significant increase every year exceeded the number of cumulative audiences of 200 million people in 2013 finally. However, starting from 2015 the Korean film industry entered a period of low growth and experienced a negative growth after all in 2016. To overcome such difficulty, stakeholders like production company, distribution company, multiplex have attempted to maximize the market returns using strategies of predicting change of market and of responding to such market change immediately. Since a film is classified as one of experiential products, it is not easy to predict a box office record and the initial number of audiences before the film is released. And also, the number of audiences fluctuates with a variety of factors after the film is released. So, the production company and distribution company try to be guaranteed the number of screens at the opining time of a newly released by multiplex chains. However, the multiplex chains tend to open the screening schedule during only a week and then determine the number of screening of the forthcoming week based on the box office record and the evaluation of audiences. Many previous researches have conducted to deal with the prediction of box office records of films. In the early stage, the researches attempted to identify factors affecting the box office record. And nowadays, many studies have tried to apply various analytic techniques to the factors identified previously in order to improve the accuracy of prediction and to explain the effect of each factor instead of identifying new factors affecting the box office record. However, most of previous researches have limitations in that they used the total number of audiences from the opening to the end as a target variable, and this makes it difficult to predict and respond to the demand of market which changes dynamically. Therefore, the purpose of this study is to predict the weekly number of audiences of a newly released film so that the stakeholder can flexibly and elastically respond to the change of the number of audiences in the film. To that end, we considered the factors used in the previous studies affecting box office and developed new factors not used in previous studies such as the order of opening of movies, dynamics of sales. Along with the comprehensive factors, we used the machine learning method such as Random Forest, Multi Layer Perception, Support Vector Machine, and Naive Bays, to predict the number of cumulative visitors from the first week after a film release to the third week. At the point of the first and the second week, we predicted the cumulative number of visitors of the forthcoming week for a released film. And at the point of the third week, we predict the total number of visitors of the film. In addition, we predicted the total number of cumulative visitors also at the point of the both first week and second week using the same factors. As a result, we found the accuracy of predicting the number of visitors at the forthcoming week was higher than that of predicting the total number of them in all of three weeks, and also the accuracy of the Random Forest was the highest among the machine learning methods we used. This study has implications in that this study 1) considered various factors comprehensively which affect the box office record and merely addressed by other previous researches such as the weekly rating of audiences after release, the weekly rank of the film after release, and the weekly sales share after release, and 2) tried to predict and respond to the demand of market which changes dynamically by suggesting models which predicts the weekly number of audiences of newly released films so that the stakeholders can flexibly and elastically respond to the change of the number of audiences in the film.

• Journal of Environmental Policy
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• v.11 no.4
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• pp.39-57
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• 2012

Analysis of the economic impact on Korean bioindustry companies was approached after Korea access to the Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits Arising from their Utilization to the Convention on Biological Diversity (hereinafter 'the Protocol') enters into force. Cost analysis of the economic impact is based on the size of bioindustry market, dependency ratio on genetic resources abroad, ABS (Access and Benefit Sharing) ratio for royalty ratio. Korean bioindustry companies would have had to pay extra ABS cost around 1.3-6.0 billion won for using genetic resources abroad, if the Protocol had entered into force in 2009. And this cost is estimated to be around 13.6 - 63.9 billion won in 2015. All ABS costs account only about less than 0.01% of total Korean bioindustry volume of target years. These show us that joining the Protocol will not significantly impact the bioindustry market in Korea. If the Protocol enters into force, genetic resources users have to pay PIC (Prior Informed Consent) and MAT (Mutually Agreed Terms) cost before accessing the genetic resources outside of their country, regardless of the accession status of the country. This ABS costs and terms on provided genetic resources will be determined by compliance between genetic resources users and providers. As a genetic resources provider, Korean bioindustry companies will have advantage over technology transfer agreements, royalties, licensing agreements, and taxes on profits from patents including traditional knowledge. Also, Korean bioindustry companies are expected to get various socio-economic benefits such as patent litigation and regulatory proceedings as a genetic resources provider. Considering the advantages and disadvantages of the Protocol that Korean bioindustry companies will face together, the socio-economic impact of the Nagoya Protocol on Korean bioindustry companies is negligible regardless of the accession status of Korea to the Nagoya Protocol.

• Journal of Service Research and Studies
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• v.6 no.2
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• pp.37-49
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• 2016

Due to the expandability of smartphone, the mobile application market is growing explosively. However, as happens in other digital contents markets, piracy of mobile applications is prevalent. This study investigated the effects of behavioral factors on smartphone application piracy. The research model consists of factors from the theory of planned behavior model - subjective norms, attitudes toward piracy and perceptions of behavioral control. In addition, perceived consequences, past behavior and habit was included. The past behavior of PC software piracy was a meaningful predictor of habit, and habit was found to influence significantly the smartphone piracy intention. The result also shows that perceived benefit had significant effect on attitude, but both perceived legal and technical risk were not significantly related to attitude. Implications for research and practice are discussed.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.127-137
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• 2014

Project Financing (PF) development project is the type which influences national economy and building industry largely because it is exerted by using borrowed money from many kinds of investors and huge amount of financial raising. Many domestic PF projects are focused mainly on the profit maximization lacking in a sufficient feasibility study. Nowadays many projects are suspending due to the global finance debacle and stagnation of real estate industry. Therefore, in this paper, risk factors of PF project are deducted and Key Success Factors (KSFs) are derived through Factor-Analysis and qualified using Fuzzy-AHP method. And through the evaluation of the derived success factors in real projects, a strong correlationship has been identified between the score of each PF success factor and the level of success and/or expected rate of return (ROR). So, the result of this paper can help decision makers of the PF projects make a better decision and give a meaningful guidance in achieving successful PF projects.

• Journal of the Korea Convergence Society
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• v.7 no.6
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• pp.205-212
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• 2016

This study attempts to empirically investigate if value strategy and momentum strategy could be improved by using past financial data such as ROE and PER in the Korean stock market. The study observes that both strategies which are refined by the portfolios consisting of companies with higher ROE/PER ratio show higher positive excessive returns than the traditional value strategy and momentum strategy. The study discusses that the excessive returns could be due to investors' behavioral biases such as conservatism, anchoring, confirmation, and herding by using convergent approach based on psychology theory. The results are not consistent with the efficient market hypothesis insisting investors' rational behavior.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.12
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• pp.1710-1720
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• 2007

Environmental changes, including intensive international competition, unpredictable consumer demand, and market trends of variety and short product life cycles, have compelled the U. S. textiles and apparel industry to focus increasingly on the consumer as a way to meet these challenges. The industry began expanding into mass customization that used information technology, flexible processes, and organizational structures to deliver a wide range of products and services that met specific needs of individual customers but on a mass scale. This paper presents cases of leading-edge technology application on customization and breakthrough concepts in personalization, with a view to raising the level of debate on these issues to its highest level.