• Journal of Wetlands Research
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• v.24 no.4
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• pp.345-353
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• 2022

A wastewater treatment plant (WWTP) is a major gateway for the engineered nano-particles (ENPs) entering the water bodies. However existing studies have reported that many WWTPs exceed the No Observed Effective Concentration (NOEC) for ENPs in the effluent and thus they need to be designed or operated to more effectively control ENPs. Understanding and predicting ENPs behaviors in the unit and \the whole process of a WWTP should be the key first step to develop strategies for controlling ENPs using a WWTP. This study aims to provide a modeling tool for predicting behaviors and removal efficiencies of ENPs in a WWTP associated with process characteristics and major operating conditions. In the developed model, four unit processes for water treatment (primary clarifier, bioreactor, secondary clarifier, and tertiary treatment unit) were considered. Additionally the model simulates the sludge treatment system as a single process that integrates multiple unit processes including thickeners, digesters, and dewatering units. The simulated ENP was nano-sized TiO₂, (nano-TiO₂) assuming that its behavior in a WWTP is dominated by the attachment with suspendid solids (SS), while dissolution and transformation are insignificant. The attachment mechanism of nano-TiO₂ to SS was incorporated into the model equations using the apparent solid-liquid partition coefficient (Kd) under the equilibrium assumption between solid and liquid phase, and a steady state condition of nano-TiO₂ was assumed. Furthermore, an MS Excel-based user interface was developed to provide user-friendly environment for the nano-TiO₂ removal efficiency calculations. Using the developed model, a preliminary simulation was conducted to examine how the solid retention time (SRT), a major operating variable affects the removal efficiency of nano-TiO₂ particles in a WWTP.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.3
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• pp.31-39
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• 2021

In this study, the fiber blending ratio and strain rate effect on the tensile properties synergy effect of hybrid fiber reinforced cement composite was evaluated. Hooked steel fiber(HSF) and smooth steel fiber(SSF) were used for reinforcing fiber. The fiber blending ratio of HSF+SSF were 1.5+0.5, 1.0+1.0 and 0.5+1.5vol.%. As a results, in the cement composite(HSF2.0) reinforced with HSF, as the strain rate increases, the tensile stress sharply decreased after the peak stress because of the decrease in the number of straightened pull-out fibers by increase of micro cracks in the matrix around HSF. When 0.5 vol.% of SSF was mixed, the micro cracks was effectively controlled at the static rate, but it was not effective in controlling micro cracks and improving the pull-out resistance of HSF at the high rate. On the other hand, the specimen(HSF1.0SSF1.0) in which 1.0vol.% HSF and 1.0vol.% SSF were mixed, each fibers controls against micro and macro cracks, and SSF improves the pull-out resistance of HSF effectively. Thus, the fiber blending effect of the strain capacity and energy absorption capacity was significantly increased at the high rate, and it showed the highest dynamic increase factor of the tensile strength, strain capacity and peak toughness. On the other hand, the incorporation of 1.5 vol.% SSF increases the number of fibers in the matrix and improves the pull-out resistance of HSF, resulting in the highest fiber blending effect of tensile strength and softening toughness. But as a low volume fraction of HSF which controlling macro crack, it was not effective for synergy of strain capacity and peak toughness.

• Journal of Appropriate Technology
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• v.7 no.2
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• pp.162-171
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• 2021

The Korean government proposed the K-SDGs in 2019 to promote the UN SDGs, but the role and tasks of science and technology, an important means of implementing the SDGs, have not been materialized. Accordingly, the role of science and technology ODA for the SDGs was established through the Ministry of Science and ICT's policy research project 'Science and Technology ODA Promotion Roadmap for Spreading the New Southern Policy and Realizing the 2030 SDGs'. In addition, goals, strategies, and core tasks for the next 10 years were derived in 10 fields such as water, climate change, energy, and ICT. In this paper, we analyze 30 key tasks of the ODA promotion roadmap for science and technology for the realization of SDGs, and propose mid- and short-term tasks and implementation plans for effective roadmap promotion. Among the key tasks in each field, four common elements were derived: ICT/smartization, a global problem-solving center, cooperation/communication platform, and business model/startup support platform/living lab that can create and integrate roadmap implementation conditions. In addition, the four mid- and short-term tasks, 1) Establishment of science and technology ODA network, 2) Establishment of living lab business platform linked to start-up support business, 3) Local smartization of recipient countries, and 4) Expand and secure sustainability of global problem-solving centers, were set in relation to the implementation of the detailed roadmap. For the derived mid- and short-term tasks, detailed implementation plans based on the ICTization of global problem-solving centers were presented. The implementation of the mid- and short-term tasks presented in this paper can contribute to the more effective achievement of the science and technology ODA roadmap, and it is expected that Korea's implementation of SDGs will also achieve high performance.

• Radiation Oncology Journal
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• v.19 no.1
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• pp.66-73
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• 2001

Purpose : For the research of Boron Neutron Capture Therapy (BNCT), fast neutrons generated from the MC-50 cyclotron with maximum energy of 34.4 MeV in Korea Cancer Center Hospital were moderated by 70 cm paraffin and then the dose characteristics were investigated. Using these results, we hope to establish the protocol about dose measurement of epi-thermal neutron, to make a basis of dose characteristic of epi-thermal neutron emitted from nuclear reactor, and to find feasibility about accelerator-based BNCT. Method and Materials : For measuring the absorbed dose and dose distribution of fast neutron beams, we used Unidos 10005 (PTW, Germany) electrometer and IC-17 (Far West, USA), IC-18, ElC-1 ion chambers manufactured by A-150 plastic and used IC-l7M ion chamber manufactured by magnesium for gamma dose. There chambers were flushed with tissue equivalent gas and argon gas and then the flow rate was S co per minute. Using Monte Carlo N-Particle (MCNP) code, transport program in mixed field with neutron, photon, electron, two dimensional dose and energy fluence distribution was calculated and there results were compared with measured results. Results : The absorbed dose of fast neutron beams was $6.47\times10^{-3}$ cGy per 1 MU at the 4 cm depth of the water phantom, which is assumed to be effective depth for BNCT. The magnitude of gamma contamination intermingled with fast neutron beams was $65.2{\pm}0.9\%$ at the same depth. In the dose distribution according to the depth of water, the neutron dose decreased linearly and the gamma dose decreased exponentially as the depth was deepened. The factor expressed energy level, $D_{20}/D_{10}$, of the total dose was 0.718. Conclusion : Through the direct measurement using the two ion chambers, which is made different wall materials, and computer calculation of isodose distribution using MCNP simulation method, we have found the dose characteristics of low fluence fast neutron beams. If the power supply and the target material, which generate high voltage and current, will be developed and gamma contamination was reduced by lead or bismuth, we think, it may be possible to accelerator-based BNCT.

• Journal of Bio-Environment Control
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• v.5 no.2
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• pp.215-235
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• 1996

The thermal analysis by mathematical model simulation makes it possible to reasonably predict heating and/or cooling requirements of certain greenhouses located under various geographical and climatic environment. It is another advantages of model simulation technique to be able to make it possible to select appropriate heating system, to set up energy utilization strategy, to schedule seasonal crop pattern, as well as to determine new greenhouse ranges. In this study, the control pattern for greenhouse microclimate is categorized as cooling and heating. Dynamic model was adopted to simulate heating requirements and/or energy conservation effectiveness such as energy saving by night-time thermal curtain, estimation of Heating Degree-Hours(HDH), long time prediction of greenhouse thermal behavior, etc. On the other hand, the cooling effects of ventilation, shading, and pad ||||&|||| fan system were partly analyzed by static model. By the experimental work with small size model greenhouse of 1.2m$\times$2.4m, it was found that cooling the greenhouse by spraying cold water directly on greenhouse cover surface or by recirculating cold water through heat exchangers would be effective in greenhouse summer cooling. The mathematical model developed for greenhouse model simulation is highly applicable because it can reflects various climatic factors like temperature, humidity, beam and diffuse solar radiation, wind velocity, etc. This model was closely verified by various weather data obtained through long period greenhouse experiment. Most of the materials relating with greenhouse heating or cooling components were obtained from model greenhouse simulated mathematically by using typical year(1987) data of Jinju Gyeongnam. But some of the materials relating with greenhouse cooling was obtained by performing model experiments which include analyzing cooling effect of water sprayed directly on greenhouse roof surface. The results are summarized as follows : 1. The heating requirements of model greenhouse were highly related with the minimum temperature set for given greenhouse. The setting temperature at night-time is much more influential on heating energy requirement than that at day-time. Therefore It is highly recommended that night- time setting temperature should be carefully determined and controlled. 2. The HDH data obtained by conventional method were estimated on the basis of considerably long term average weather temperature together with the standard base temperature(usually 18.3$^{\circ}C$). This kind of data can merely be used as a relative comparison criteria about heating load, but is not applicable in the calculation of greenhouse heating requirements because of the limited consideration of climatic factors and inappropriate base temperature. By comparing the HDM data with the results of simulation, it is found that the heating system design by HDH data will probably overshoot the actual heating requirement. 3. The energy saving effect of night-time thermal curtain as well as estimated heating requirement is found to be sensitively related with weather condition: Thermal curtain adopted for simulation showed high effectiveness in energy saving which amounts to more than 50% of annual heating requirement. 4. The ventilation performances doting warm seasons are mainly influenced by air exchange rate even though there are some variations depending on greenhouse structural difference, weather and cropping conditions. For air exchanges above 1 volume per minute, the reduction rate of temperature rise on both types of considered greenhouse becomes modest with the additional increase of ventilation capacity. Therefore the desirable ventilation capacity is assumed to be 1 air change per minute, which is the recommended ventilation rate in common greenhouse. 5. In glass covered greenhouse with full production, under clear weather of 50% RH, and continuous 1 air change per minute, the temperature drop in 50% shaded greenhouse and pad ＆ fan systemed greenhouse is 2.6$^{\circ}C$ and.6.1$^{\circ}C$ respectively. The temperature in control greenhouse under continuous air change at this time was 36.6$^{\circ}C$ which was 5.3$^{\circ}C$ above ambient temperature. As a result the greenhouse temperature can be maintained 3$^{\circ}C$ below ambient temperature. But when RH is 80%, it was impossible to drop greenhouse temperature below ambient temperature because possible temperature reduction by pad ||||&|||| fan system at this time is not more than 2.4$^{\circ}C$. 6. During 3 months of hot summer season if the greenhouse is assumed to be cooled only when greenhouse temperature rise above 27$^{\circ}C$, the relationship between RH of ambient air and greenhouse temperature drop($\Delta$T) was formulated as follows : $\Delta$T= -0.077RH＋7.7 7. Time dependent cooling effects performed by operation of each or combination of ventilation, 50% shading, pad ＆ fan of 80% efficiency, were continuously predicted for one typical summer day long. When the greenhouse was cooled only by 1 air change per minute, greenhouse air temperature was 5$^{\circ}C$ above outdoor temperature. Either method alone can not drop greenhouse air temperature below outdoor temperature even under the fully cropped situations. But when both systems were operated together, greenhouse air temperature can be controlled to about 2.0-2.3$^{\circ}C$ below ambient temperature. 8. When the cool water of 6.5-8.5$^{\circ}C$ was sprayed on greenhouse roof surface with the water flow rate of 1.3 liter/min per unit greenhouse floor area, greenhouse air temperature could be dropped down to 16.5-18.$0^{\circ}C$, whlch is about 1$0^{\circ}C$ below the ambient temperature of 26.5-28.$0^{\circ}C$ at that time. The most important thing in cooling greenhouse air effectively with water spray may be obtaining plenty of cool water source like ground water itself or cold water produced by heat-pump. Future work is focused on not only analyzing the feasibility of heat pump operation but also finding the relationships between greenhouse air temperature(T$_{g}$ ), spraying water temperature(T$_{w}$ ), water flow rate(Q), and ambient temperature(T$_{o}$).

• Korean Journal of Soil Science and Fertilizer
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• v.10 no.1
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• pp.61-67
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• 1977

A study was conducted in order to compare the topdressing method of the conventional fertilizers as control and the deep application method of the ball complex fertilizer newly developed. The ball complex fertilizer consisted of 5% of nitrogen, 5% of phosphorus, and 7% of potassium. Basal application of nitrogen for the rice plant was the same for both control plots and ball complex plots. One ball complex fertilizer per four hills was applied at depth of 12~13cm 35days before heading stage while control plot received three times topdressing at different growth stages as usual practice. The results obtained were as follows. 1. The ball complex fertilizer applied in the soil was continuously utilized by the rice plants until harvest time while nitrogen and potassium uptake of control plots was reduced rapidly after heading stage. Daily uptake of nitrogen and potassium per hill at maturing stage were 0.45mg and 0.68mg in control plots, but 4.80mg and 7.0mg respectively in ball complex plots. 2. Dry matter productivity of the rice plant in control plots, well coinciding with nutrients uptake pattern, was maximum just after heading stage decreased at maturing stage. But dry matter productivity in ball complex plots was much higher at maturing stage than at heading stage. 3. Ball complex application increased effective tillering rate, causing higher panicle number per hill. 4. Ball complex application brought about 528kg/10a of hulled grain yield while the conventional practice 423kg/10a. 5. Deep application of ball complex was superior to usual practice in terms of yield components such as panicle number per hill, filled grain number per panicle, maturing rate, and 1,000 grain weight. 6. From the morphological characteristics point of view, the deep application of ball complex made the flag leaf and the 2nd leaf heavier, larger and broader as compared to control treatment. 7. It is considered that by applying the ball complex fertilizer at depth of 12~13cm sufficient amount of nitrogen and potassium could be utilized by rice plants during the maturing stage and assimilated in the leaf blade, consequently making the flag leaf and the 2nd leaf bigger and healthier. The fact can easily explain that the ball complex plots had higher capacity of photosynthesis, less discoloration of lower leaves, bigger leaf area index, and better grain yield as compared to the conventional practice. In conclusion the deep application method of the ball complex fertilizer was superior to the routine topdressing method of the usual fertilizers.

• Journal of the korean academy of Pediatric Dentistry
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• v.26 no.2
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• pp.377-398
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• 1999

Calcium fluoride, created by topical fluoride application, is the reservoir for fluoride ion regulated by pH in the oral environment. Therefore, the amount and the maintenance of calcium fluoride have an important role in preventing dental caries. The aim of this study is to evaluate the effect of Nd:YAG laser irradiation on the generation of calcium fluoride and the acid resistance of tooth enamel. The bovine anterior permanent teeth were prepared (n=276), and divided into following groups : no treatment (control) fluoride application alone, laser irradiation alone, laser irradiation after fluoride application, and fluoride application after laser irradiation. And each group was subdivided based on the application time of 1.23% acidulated phosphate fluoride (APF) (5 min and 30 min) and the irradiation energy of Nd:YAG laser ($20J/cm^2\;and\;40J/cm^2$). In case of fluoride application, each group was divided according to KOH treatment. Twenty three treatment conditions were made for this experiment and twelve specimens were assigned to each treatment condition. In each treatment condition, ten specimens were used for chemical analysis and two specimens were observed under SEM. In groups without treating KOH, fluoride content and the depth of enamel dissolved were measured using enamel biopsy technique. In groups with treating KOH, the amount of calcium fluoride was measured by the treatment with 1 M KOH for 24 hours and enamel biopsy was performed after KOH treatment. The results were analyzed by the fluoride content and the depth of enamel dissolved by enamel biopsy, amount and thickness of calcium fluoride, and the surface structures of enamel. The results are as follows: 1. In groups without treating KOH, the fluoride content of removed enamel showed a positive relationship with the energy density of laser when the laser irradiated before fluoride application 2. In groups without treating KOH, the depth of enamel dissolved decreased more with the combined laser and fluoride treatment than with laser or fluoride treatment, except for the case of $20J/cm^2$ laser irradiation after 5 minute fluoride application (p<0.05). 3. The amount of calcium fluoride did not increased by laser treatment with no statistical significance(p>0.05). 4. The particle size of calcium fluoride increased in case of fluoride treatment after laser irradiation, compared with fluoride application alone. In case of laser treatment after fluoride application, the particle size of calcium fluoride increased and some of the particles fused as well. 5. There were no significant differences in the fluoride content of dissolved enamel between groups without treating KOH and control group, except for the case of laser irradiation after treatment of APF for 30 minutes (p>0.05). 6. In groups with treating KOH, depth of removed enamel in the groups of combined treatment with laser and fluoride was shallower than that in fluoride application groups (p<0.05). 7. In groups without treating KOH, the relationship between fluoride content and the depth of enamel dissolved showed more negative (Spearman correlation coefficient: -0.6281) than in groups with treating KOH (Spearman correlation coefficient: -0.3792). The greater amount of calcium fluoride could be found in case where there was a significant differences of the depth of enamel dissolved between groups with and without treating KOH. From these results, it can be concluded that laser seems to be a little effects on the amount of calcium fluoride formation, but has some effect on the lowering the solubility of calcium fluoride. As the combined treatment of laser and fluoride application showed more effective acid-resistant property, more extended recall period for fluoride application can be achieved with this combined treatment in the clinic.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.6
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• pp.317-322
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• 2016

While PFOS sodium salt ($C_8F_{17}SO_3Na$) was not degraded by microorganisms for 28 days, the 4 alternatives were biodegraded at the rates of 21.6% for $C_{25}F_{17}H_{32}S_3O_{13}Na_3$, 20.5% for $C_{15}F_9H_{21}S_2O_8Na_2$, 15.8% for $C_{23}F_{18}H_{28}S_2O_8Na_2$ and 6.4% for $C_{17}F_9H_{25}S_2O_8Na_2$, respectively. The acute toxicity test using Daphnia magna was conducted for 48 hours, the half effective concentration ($EC_{50}$) of PFOS sodium salt ($C_8F_{17}SO_3Na$) was evaluated in 54.5 mg/L. While the 4 alternatives did not show any effect at 500.0 mg/L. The surface tension of the PFOS salt ($C_8F_{17}SO_3Na$) is 46.2 mN/m at a concentration of 500.0 mg/L. While the surface tension of the 4 alternatives was found to be superior to PFOS sodium salt ($C_8F_{17}SO_3Na$). The surface tension of $C_{23}F_{18}H_{28}S_2O_8Na_2$ (20.9 mN/m) has the lowest, followed by $C_{15}F_9H_{21}S_2O_8Na_2$ (23.4 mN/m), $C_{17}F_9H_{25}S_2O_8Na_2$ (27.3 mN/m), $C_{25}F_{17}H_{32}S_3O_{13}Na_3$ (28.2 mN/m). The four kinds of alternatives ($C_{15}F_9H_{21}S_2O_8Na_2$, $C_{17}F_9H_{25}S_2O_8Na_2$, $C_{23}F_{18}H_{28}S_2O_8Na_2$, $C_{25}F_{17}H_{32}S_3O_{13}Na_3$) were found to be superior to PFOS sodium salt ($C_8F_{17}SO_3Na$) in terms of biodegradation, Daphnia sp. acute toxicity and surface tension, and thus they were considered applicable as PFOS alternatives. Especially biodegradation rate of $C_{15}F_9H_{21}S_2O_8Na_2$, $C_{23}F_{18}H_{28}S_2O_8Na_2$ and $C_{25}F_{17}H_{32}S_3O_{13}Na_3$ was relatively high as 15.8~21.6%, and Daphnia sp. acute toxicity and surface tension were considerably superior (surface tension 39~55%) to PFOS sodium salt. Therefore, these alternatives are considered to be available as an alternative of PFOS.

• Journal of Technology Innovation
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• v.17 no.1
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• pp.1-48
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• 2009

Recently we have found some symptoms that R&D fiscal incentives might not work well what it has intended through the analysis of current statistics of firm's R&D data. Firstly, we found that the growth rate of R&D investment in private sector during the recent decade has been slowdown. The average of growth rate (real value) of R&D investment is 7.1% from 1998 to 2005, while it was 13.9% from 1980 to 1997. Secondly, the relative share of R&D investment of SME has been decreased to 21%('05) from 29%('01), even though the tax credit for SME has been more beneficial than large size firm, Thirdly, The R&D expenditure of large size firms (besides 3 leading firms) has not been increased since late of 1990s. We need to find some evidence whether fiscal incentives are effective in increasing firm's R&D investment. To analyse econometric model we use firm level unbalanced panel data for 4 years (from 2002 to 2005) derived from MOST database compiled from the annual survey, "Report on the Survey of Research and Development in Science and Technology". Also we use fixed effect model (Hausman test results accept fixed effect model with 1% of significant level) and estimate the model for all firms, large firms and SME respectively. We have following results from the analysis of econometric model. For large firm: i ) R&D investment responds elastically (1.20) to sales volume. ii) government R&D subsidy induces R&D investment (0.03) not so effectively. iii) Tax price elasticity is almost unity (-0.99). iv) For large firm tax incentive is more effective than R&D subsidy For SME: i ) Sales volume increase R&D investment of SME (0.043) not so effectively. ii ) government R&D subsidy is crowding out R&D investment of SME not seriously (-0.0079) iii) Tax price elasticity is very inelastic (-0.054) To compare with other studies, Koga(2003) has a similar result of tax price elasticity for Japanese firm (-1.0036), Hall((l992) has a unit tax price elasticity, Bloom et al. (2002) has $-0.354{\sim}-0.124$ in the short run. From the results of our analysis we recommend that government R&D subsidy has to focus on such an areas like basic research and public sector (defense, energy, health etc.) not overlapped private R&D sector. For SME government has to focus on establishing R&D infrastructure. To promote tax incentive policy, we need to strengthen the tax incentive scheme for large size firm's R&D investment. We recommend tax credit for large size film be extended to total volume of R&D investment.