• Title/Summary/Keyword: 비용지수

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Improvement of Performance Test Standards for Marine Pollution Prevention Materials and Chemicals (for Eco-toxicity Test) (해양오염방제 자재·약제의 성능시험기준 개선방안에 관한 연구(생태독성시험 항목))

  • Kim, Tae Won;Lee, Su Jin;Kim, Young Ryun;Lee, Moon Jin
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.6
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    • pp.744-753
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    • 2021
  • This study suggests ways to improve the standard test method and judgment criterion for the "Eco-toxicity Test" based on the rules and regulations provided in 'performance and qualifying test standards for marine pollution prevention materials and chemicals' in the Republic of Korea. Compared with the relevant references of other countries, this study attempted to find the limitations in the existing standards. As for the growth inhibition test of algae using Skeletonema costatum as an indicator, applying comparative analysis to measure specific growth rates, together with statistical analysis, instead of applying current methods, judged by the appearance of colors from the culture medium was suggested. Considering the exponential growth phase of the test species, the test duration was suggested to be reduced to less than four days. For the test with fish as an indicator, resetting the appropriate body size was suggested to, show consistent sensitivity against chenicals applied during testing. Furthermore, it is necessary to consider the criteria needs, which should be established in reasonable and objective ways. For the testing species, marine rotifer, Brachionus plicatilis could be a replacement for Artemia sp., and a bivalve for fish in the test. To improve the performance effectiveness of the "Eco-toxicity test", it is worth considering the designation of accredited testing institutes, by placing it in the same loop. Thus it is also expected to have a reliable management system in place, having the capacity of cost calculation properly and adjusting testing items if required.

Factor Prices and Markup in the Korean Manufacturing Industry: An Empirical Analysis 1975-2007 (한국의 생산요소가격 변화가 마크업의 변동에 미치는 영향에 관한 실증분석: 1975-2007)

  • Kang, Joo Hoon;Park, Sehoon
    • International Area Studies Review
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    • v.15 no.2
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    • pp.77-100
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    • 2011
  • The Korean economy have experienced the remarkable decreases in factor prices such as bond yields, real wage since the IMF foreign exchange crisis. This paper investigates the effects of the price changes in the factor markets on determining the level and cyclicality of industrial markups in the manufacturing industry. For this purpose, we construct a markup equation in the small open economy based on the production function including foreign intermediate goods and assuming constant returns to scale technology and AR(1) process of technological coefficient. Empirical results are summarized as the followings. The empirical results shows that the increased markups after the IMF crisis can be explained by the price decreases in the factor markets which result in lowering marginal costs. And we also observed counter cyclicality of markup, labor share and interest rates while real wages, technical coefficients, and production price index proved to be pro-cyclical. In conclusion, the price changes in factor market have contributed to the stickiness in markup fluctuation in the manufacturing industry.

A Study on Factors Determining the M&A and Greenfield of Korean Firms in China (한국기업의 대(對)중국 M&A 및 신설투자에 영향을 미치는 요인에 관한 비교 연구)

  • Choi, Baek Ryul
    • International Area Studies Review
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    • v.15 no.2
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    • pp.247-273
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    • 2011
  • This study analyzes the impacts on the M&A and greenfield of macroeconomic variables of home and host countries, after identifying current status and characteristics of the M&A and greenfield related to the entering way of Korean firms in China. Main empirical results are summarize as follows. First, as for foreign exchange variable, the decreased value of Korea won shows the negative correlations with both of the greenfield and M&A. Second, the real interest rate of Korea to measure the cost of capital is not significant statistically. Third, while the host country's stock market index, Shanghai Comprehensive Index, shows the expected negative correlations with the investment in the case of small & medium firm and light industry, it shows the positive correlations which is not consistent with general expectation in the case of large firm and heavy industry. Fourth, the openness of host country shows the positive correlations with both of the greenfield and M&A. Finally, in regard to the M&A, China's GDP to measure the market size of host country is not significant statistically while it shows the strong positive relationship with the greenfield investment.

Development of a Conceptual Estimate Methodology for Plant Construction Projects (플랜트 건설 프로젝트를 위한 개산견적 방법론 개발)

  • Kim, Hyun-Joong;Choi, Jaehyun
    • Korean Journal of Construction Engineering and Management
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    • v.20 no.1
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    • pp.141-150
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    • 2019
  • In the overseas plant construction market, the domain construction firms' construction capability has been greatly improved, but the capability of project management is evaluated to be insufficient compared to the technical aspect. Project management capabilities from the initial planning stage of project execution are regarded as the core competence of advanced construction companies. Among them, it is urgent to improve the capacity of conceptual estimate for domestic companies. In this study, the researchers surveyed and analyzed the methodology of estimating project cost in the planning phase of the plant project and developed an estimation method by conducting a case study analysis. Based on the logic of the cost index and parametric estimation method among the existing estimation methodology, the estimation tool was developed by deriving the input and output variables tailored to the plant project. The validity of the proposed methodology was evaluated by comparing the accuracy between the project estimate amount of the case project and the actual project amount. In order to increase the utilization of the developed conceptual estimate methodology,for plant construction project, it is necessary to systematize the data of the historical project data. Increasing the accuracy of future project cost estimates is directly related to increasing project award and profitability of the domestic construction company.

A Study on Measuring Urban Sprawl and Its Policy Implications for Urban Growth Management and Urban Regeneration in Seoul Capital Region (수도권 도시 스프롤 평가에 따른 도시성장관리 및 도시재생 정책 방향에 관한 연구)

  • Jeon, Hye-Jin;Woo, Myungje
    • Journal of the Korean Regional Science Association
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    • v.35 no.1
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    • pp.3-18
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    • 2019
  • Urban sprawl has been criticized due to its negative effects, including the encroachment of farmland and open spaces, the increase in traffic congestion and air pollution, the decline of central city, the decrease in social capital, and the unfairness of tax burdens on infrastructure and public services. This study measures urban sprawl in the capital region of South Korea where the characteristics of urban sprawl have been known to be different from those identified in the U.S. metropolitan areas. In particular, the study examines whether the capital region has experienced the decline of the central city with an expansion of low density residential development in suburban areas. Three measurements, the sprawl index with population density, the ratio of changes in urbanized areas to changes in population, and the population density gradient, were employed to measure urban sprawl, and GIS mapping and descriptive analysis were used to examine the central city decline and the characteristics of development patterns in suburban areas. The results show that the capital region of South Korea is moving to the American style sprawled development with the decline of the central city and an increase of single detached homes in suburban areas, implying that policy makers need to develop growth management strategies to prevent urban sprawl and its negative effects that many U.S. metropolitan areas have suffered from.

A Study on the Yield Rate and Risk of Portfolio Combined with Real Estate Indirect Investment Products (부동산간접투자상품이 결합된 포트폴리오의 수익률과 위험에 관한 연구)

  • Choi, Suk-Hyun;Kim, Jong-Jin
    • Journal of Cadastre & Land InformatiX
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    • v.49 no.1
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    • pp.45-63
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    • 2019
  • Until recently, most people have invested in a traditional portfolio consisting of stocks, bonds and real estates based on the three-division method of properties in Korea. However, this study analyzed the impact of the composition of a portfolio combining representative real estate indirect investment products such as Reits and real estate funds on the investment performance. For this purpose, the empirical analysis using the mean variance model, which is the most appropriate method for the portfolio composition, was used. For variables used in this study, mixed asset portfolios were classified into Portfolio A through Portfolio G depending on the composition of assets, and the price indices selected as Kospi, Krx bond, Reits Trus Y7, Hanwha-Lasal fund, and Office (Seoul). The results are as follows; first Portfolio D, which combined bonds, stocks, Reits and Real Estate funds, and Portfolio G, which added the office, the actual real estate, were shown to have the lowest risk. second, Portfolio B composed of bonds, stocks and Reits and Portfolio D with added real estate funds had the lowest risk while Portfolio F composed of bonds, stocks, offices and real estate funds, and Portfolio G with added Reits were the most profitable. As a result, it has been analyzed that it was more effective to compose a portfolio including Reits and real estate funds, which were real estate indirect investment products that eliminated the illiquidity limitation of real estates than real estates, the traditional three-division method of properties. Therefore, it is possible to minimize the risk of investors and reduce the cost of ownership of the real estate by solving the illiquidity problem that is the biggest disadvantage of the direct investment, In addition, it is considered that it is more necessary to reinvigorate the real estate indirect investment market where small amounts can be invested.

A Study on Technological Forecasting for Promising Alternative Technologies Using Fisher-Pry Modification Model (Fisher-Pry 수정모형을 활용한 유망대체기술 예측에 관한 연구)

  • Hong, Sung-Il;Kim, Byung-Nam
    • The Journal of the Korea Contents Association
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    • v.19 no.5
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    • pp.104-114
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    • 2019
  • In the global market competition, countries and businesses are actively engaged in technology prediction activities to maximize their profits by attempting to enter and preempting the core technology of the future. In this paper, we propose a growth model based on patent application trends to predict the time to replace a product with a promising new technology to dominate the market. Although the Fisher-Pry model that Bhargava generalized to predict the emergence of promising alternative technologies was relatively satisfactory compared to the original Fisher-Pry model, it was difficult to predict the replacement rate behavior properly due to a parameter problem. The application of the Fisher-Pry Modification Model in the form of a quadratic equation through the patent trend analysis of the optical storage system for the purpose of verifying the time alternative to the light storage technology has resulted in satisfactory verification results. It is expected that small and medium-sized companies and individual researchers will apply this model and use it more easily to predict the time to replace the market for promising replacement technologies.

The Effects of Fertilization on Growth Performances and Physiological Characteristics of Liriodendron tulipifera in a Container Nursery System (시비 처리가 백합나무 용기묘의 생장 및 생리적 특성에 미치는 영향)

  • Cho, Min Seok;Lee, Soo Won;Park, Byung Bae;Park, Gwan Su
    • Journal of Korean Society of Forest Science
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    • v.100 no.2
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    • pp.305-313
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    • 2011
  • Fertilization is essential to seedling production in nursery culture, but excessive fertilization can contaminate surface and ground water around the nursery. The objective of this study was to find optimal fertilization practice of container seedling production for reducing soil and water contamination around the nursery without compromising seedling quality. This study was conducted to investigate growth performance, photosynthesis, chlorophyll fluorescence, and chlorophyll contents of Liriodendron tulipifera growing under three different fertilization treatments (Constant rate, Three-stage rate, and Exponential rate fertilization). Root collar diameter, height, and biomass of L. tulipifera were the highest at Constant treatment. Like growth performance, seedling quality index (SQI) were higher at Constant than at other treatments, but not significantly different among treatments. L. tulipifera showed good photosynthetic capacity at all treatments. Photochemical efficiency and chlorophyll contents were significantly lower at Exponential than at other treatments. Therefore, Exponential fertilization which is 50% fertilizer of other treatments would maximize seedling growth and minimize nutrient loss.

Learning Data Model Definition and Machine Learning Analysis for Data-Based Li-Ion Battery Performance Prediction (데이터 기반 리튬 이온 배터리 성능 예측을 위한 학습 데이터 모델 정의 및 기계학습 분석 )

  • Byoungwook Kim;Ji Su Park;Hong-Jun Jang
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.3
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    • pp.133-140
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    • 2023
  • The performance of lithium ion batteries depends on the usage environment and the combination ratio of cathode materials. In order to develop a high-performance lithium-ion battery, it is necessary to manufacture the battery and measure its performance while varying the cathode material ratio. However, it takes a lot of time and money to directly develop batteries and measure their performance for all combinations of variables. Therefore, research to predict the performance of a battery using an artificial intelligence model has been actively conducted. However, since measurement experiments were conducted with the same battery in the existing published battery data, the cathode material combination ratio was fixed and was not included as a data attribute. In this paper, we define a training data model required to develop an artificial intelligence model that can predict battery performance according to the combination ratio of cathode materials. We analyzed the factors that can affect the performance of lithium-ion batteries and defined the mass of each cathode material and battery usage environment (cycle, current, temperature, time) as input data and the battery power and capacity as target data. In the battery data in different experimental environments, each battery data maintained a unique pattern, and the battery classification model showed that each battery was classified with an error of about 2%.

Efficient IoT data processing techniques based on deep learning for Edge Network Environments (에지 네트워크 환경을 위한 딥 러닝 기반의 효율적인 IoT 데이터 처리 기법)

  • Jeong, Yoon-Su
    • Journal of Digital Convergence
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    • v.20 no.3
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    • pp.325-331
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    • 2022
  • As IoT devices are used in various ways in an edge network environment, multiple studies are being conducted that utilizes the information collected from IoT devices in various applications. However, it is not easy to apply accurate IoT data immediately as IoT data collected according to network environment (interference, interference, etc.) are frequently missed or error occurs. In order to minimize mistakes in IoT data collected in an edge network environment, this paper proposes a management technique that ensures the reliability of IoT data by randomly generating signature values of IoT data and allocating only Security Information (SI) values to IoT data in bit form. The proposed technique binds IoT data into a blockchain by applying multiple hash chains to asymmetrically link and process data collected from IoT devices. In this case, the blockchainized IoT data uses a probability function to which a weight is applied according to a correlation index based on deep learning. In addition, the proposed technique can expand and operate grouped IoT data into an n-layer structure to lower the integrity and processing cost of IoT data.