• The Korean Journal of Nuclear Medicine
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• v.31 no.1
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• pp.19-29
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• 1997

Recently, [I-123]IPT SPECT has been used for early diagnosis of Parkinson's patients(PP) by imaging dopamine transporters. The dynamic time activity curves in basal ganglia(BG) and occipital cortex(OCC) without blood samples were obtained for 2 hours. These data were then used to measure dopamine transporters by operationally defined ratio methods of (BG-OCC)/OCC at 2 hrs, binding potential $R_v=k_3/k_4$ using graphic method or $R_A$= (ABBG-ABOCC)/ABOCC for 2 hrs, where ABBG represents accumulated binding activity in basal ganglia(${\int}^{120min}_0$ BG(t)dt) and ABOCC represents accumulated binding activity in occipital cortex(${\int}^{120min}_0$ OCC(t)dt). The purpose of this study was to examine the IPT pharmacokinetics and investigate the usefulness of simplified methods of (BG-OCC)/OCC, $R_A$, and $R_v$ which are often assumed that these values reflect the true values of $k_3/k_4$. The rate constants $K_1,\;k_2\;k_3$ and $k_4$ to be used for simulations were derived using [I-123]IPT SPECT and aterialized blood data with a standard three compartmental model. The sensitivities and time activity curves in BG and OCC were computed by changing $K_l$ and $k_3$(only BG) for every 5min over 2 hours. The values (BG-OCC)/OCC, $R_A$, and $R_v$ were then computed from the time activity curves and the linear regression analysis was used to measure the accuracies of these methods. The late constants $K_l,\;k_2\;k_3\;k_4$ at BG and OCC were $1.26{\pm}5.41%,\;0.044{\pm}19.58%,\;0.031{\pm}24.36%,\;0.008{\pm}22.78%$ and $1.36{\pm}4.76%,\;0.170{\pm}6.89%,\;0.007{\pm}23.89%,\;0.007{\pm}45.09%$, respectively. The Sensitivities for ((${\Delta}S/S$)/(${\Delta}k_3/k_3$)) and ((${\Delta}S/S$)/(${\Delta}K_l/K_l$)) at 30min and 120min were measured as (0.19, 0.50) and (0.61, 0,23), respectively. The correlation coefficients and slopes of ((BG-OCC)/OCC, $R_A$, and $R_v$) with $k_3/k_4$ were (0.98, 1.00, 0.99) and (1.76, 0.47, 1.25), respectively. These simulation results indicate that a late [I-123]IPT SPECT image may represent the distribution of the dopamine transporters. Good correlations were shown between (3G-OCC)/OCC, $R_A$ or $R_v$ and true $k_3/k_4$, although the slopes between them were not unity. Pharmacokinetic computer simulations may be a very useful technique in studying dopamine transporter systems.

• Journal of Korean Society of Forest Science
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• v.81 no.4
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• pp.337-345
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• 1992

In this research, a kinematic wave model was applied for the runoff analysis, Regulation of streamflow was estimated by the calibration of roughness coefficient as a parameter. The data analyzed were obtained from Ananomiya and Shirasaka experimental basins at Tokyo University Forest in Aichi. Estimation methods and characteristics of roughness coefficient as a evaluation method of hydrological function of forest are summarized as follows ; 1. Roughness coefficient($N_s$) indicates the resistance of hillslope to the flowing water of surface runoff. There exists an hypothesis that resistance of hillslope to flowing water increase with the growth forest and development of the $A_o$ layer. 2. Roughness coefficient($N_s$) was estimated by the parameter when the stream direct runoff was calculated by using the kinematic wave. 3. Secular change of '$N_s$' in ananomiya has a curve which has an upper limit and increases exponentially near the limit. The curve quickly increased from 1935 to 1945 when results of afforestation for erosion control were thought to be effective. On the other hand, slight increase of '$N_s$' in Shirasaka indicates that there was not such a big change in the surface of soil layer. 4. The increase of '$N_s$' was related with decrease of direct runoff and increase of base flow. It was recognized that the rate of direct runoff decreased with the improvement of forest physiognomy and the rate of base flow was increased. But absolute value of water runoff per one storm decreased in chronological order.

• Progress in Medical Physics
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• v.20 no.4
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• pp.191-198
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• 2009

In this study, we evaluated an edge detector for small-beam dosimetry. We measured the dose linearity, dose rate dependence, output factor, beam profiles, and percentage depth dose using an edge detector (Model 1118 Edge) for 6-MV photon beams at different field sizes and depths. The obtained values were compared with those obtained using a standard volume ionization chamber (CC13) and photon diode detector (PFD). The dose linearity results for the three detectors showed good agreement within 1%. The edge detector had the best linearity of ${\pm}0.08%$. The edge detector and PFD showed little dose rate dependency throughout the range of 100~600 MU/min, while CC13 showed a significant discrepancy of approximately -5% at 100 MU/min. The output factors of the three detectors showed good agreement within 1% for the tested field sizes. However, the output factor of CC13 compared to the other two detectors had a maximum difference of 21% for small field sizes (${\sim}4{\times}4\;cm^2$). When analyzing the 20~80% penumbra, the penumbra measured using CC13 was approximately two times wider than that using the edge detector for all field sizes. The width measured using PFD was approximately 30% wider for all field sizes. Compared to the edge detector, the 10~90% penumbras measured using the CC13 and PFD were approximately 55% and 19% wider, respectively. The full width at half maximum (FWHM) of the edge detector was close to the real field size, while the other two detectors measured values that were 8~10% greater for all field sizes. Percentage depth doses measured by the three detectors corresponded to each other for small beams. Based on the results, we consider the edge detector as an appropriate small-beam detector, while CC13 and PFD can lead to some errors when used for small beam fields under $4{\times}4\;cm^2$.

• Journal of Technology Innovation
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• v.22 no.1
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• pp.149-175
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• 2014

This study analyzed the effect of corporate innovation strategies on patent production and ultimately on technological change and new product development of firms in South Korea. The intent was to derive efficient strategies for enhancing technological performance of the firms. For the empirical analysis, three sources of data were combined: four waves of the Human Capital Corporate Panel Survey (HCCP) data collected by the Korea Research Institute for Vocational Education and Training (KRIVET), corporate financial data obtained from the Korea Information Service (KIS), and corporate patent data provided by the Korean Intellectual Property Office (KIPO). The patent production function was estimated by zero-inflated negative binomial (ZINB) regression. The technological performance function was estimated by two-stage regression, taking into account the endogeneity of patent production. An ordered logit model was applied for the second stage regression. Empirical results confirmed the critical role of corporate innovation strategies in patent production and in facilitating technological change and new product development of the firms. In patent production, the firms' R&D investment and human resources were key determinants. Higher R&D intensity led to more patents, yet with decreasing marginal productivity. A larger stock of registered patents also led to a larger flow of new patent production. Firms were more prolific in patent production when they had high-quality personnel, intensely investing in human resource development, and adopting market-leading or fast-follower strategy as compared to stability strategy. In technological performance, the firms' human resources played a key role in accelerating technological change and new product development. R&D intensity expedited new product development of the firm. Firms adopting market-leading or fast-follower strategy were at an advantage than those with stability strategy in technological performance. Firms prolific in patent production were also advanced in terms of technological change and new product development. However, the nexus between patent production and technological performance measures was substantially reduced when controlling for the endogeneity of patent production. These results suggest that firms need to strengthen the linkage between patent production and technological performance, and take strategies that address each firm's capacities and needs.

• Journal of the Mineralogical Society of Korea
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• v.7 no.1
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• pp.62-79
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• 1994

The quanttative and structural analysis of the binary standard mixtures of albite and quartz, and microcline and albite were carried out using the Rietveld refinement method in order to investigate the accuracy and precision of the method. The quantitative analysis using the Rietveld method results in a standard deviation of 4 wt % for the albite-quartz standard mixtures and 1 wt % for the microcline-albite standard mixtures, suggesting that its accuracy is far better than that of the conventional XRD method in which only a few selected peaks are utilized. Furthermore, the unit-cell parameters of component minerals in mixtures were also estimated accurately during the analysis. It was observed that the refined weight fractions deviate systematically from their measured values when the method is applied to the mixtures that contain minerals with different degrees of preferred orientation, such as albite-quartz mixtures. The preferred orientation parameters and R-values suggest that the systematic deviation is caused as a result of the preferred orientation effect of feldspar crystallites. It is evident that the preferred orientation corrections are of help for the accurate determination of unit-cell parameters, although they may not improve the result of quantitative analysis significantly. The refined weight fraction of the mineral with higher degree of preferred orientation in mixture is greater than the measured one. This is apparently caused by the effect of geometry of feldspar crystallites in the surface of the mounted sample. The Rietveld refinement method minimizes the problems inherent in the traditional XRD methods, such as the line overlap, primary extinction, and preferred orientation effect, by fitting every data point in a whole pattern explicitly. Furthermore, accurate unit-cell parameters as well as scale factors that can be obtained from the Rietveld refinement are used for the quqantification. The present stdudy demonstrates that the Rietveld method yields far more accurate analytical result than the conventional XRD quantitative analysis method does.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.267-282
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• 2018

Despite the continuous development of phenology detection studies using satellite imagery, verification through comparison with the field observed data is insufficient. Especially, in the case of Korean forests patching in various forms, it is difficult to estimate the start of season (SOS) by using only satellite images due to resolution difference. To improve the accuracy of vegetation phenology estimation, this study reconstructed the large scaled forest type map (1:5,000) with MODIS pixel resolution and produced time series vegetation phenology curves from Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) derived from MODIS images. Based on the field observed data, extraction methods for the vegetation indices and SOS for Korean forests were compared and evaluated. We also analyzed the correlation between the composition ratio of forest types in each pixel and phenology extraction from the vegetation indices. When we compared NDVI and EVI with the field observed SOS data from the Korea National Arboretum, EVI was more accurate for Korean forests, and the first derivative was most suitable for extracting SOS in the phenology curve from the vegetation index. When the eight pixels neighboring the pixels of 7 broadleaved trees with field SOS data (center pixel) were compared to field SOS, the forest types of the best pixels with the highest correlation with the field data were deciduous forest by 67.9%, coniferous forest by 14.3%, and mixed forest by 7.7%, and the mean coefficient of determination ($R^2$) was 0.64. The average national SOS extracted from MODIS EVI were DOY 112.9 in 2014 at the earliest and DOY 129.1 in 2010 at the latest, which is about 0.16 days faster since 2003. In future research, it is necessary to expand the analysis of deciduous and mixed forests' SOS into the extraction of coniferous forest's SOS in order to understand the various climate and geomorphic factors. As such, comprehensive study should be carried out considering the diversity of forest ecosystems in Korea.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.69-69
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• 2011

태양열 발전 플랜트에 사용되는 중고온 범위의 축열조에 고체-액체간 상변화를 수행하는 용융염을 축열물질로 사용하면 액체상 또는 고체상만으로 된 열저장 매체에 비해 축열조의 규모를 축소함과 동시에 축열온도의 균일성 향상에 기여할 수 있다. 중온인 $250{\sim}400^{\circ}C$ 범위에서 이용 가능한 용융염으로는 질산칼륨($KNO_3$), 질산리튬($LiNO_3$)등이 있다. 그러나 이러한 용융염의 가장 큰 단점은 열전도율이 매우 낮다는 것이며, 이로 인해 요구되는 열전달률을 성취하기 위해서는 많은 열접촉면적이 필요하다는 것이다. 이러한 단점을 극복하는 방법을 도입하지 않고서는 축열시스템의 소규화를 성취하는데 큰 효과를 가져올 수 없다. 한편 열수송 성능이 탁월한 히트파이프를 사용하면 열원 및 열침과 축열물질 사이의 열전달 효율을 증가시켜 시스템의 성능 향상과 동시에 소규모화에 기여할 수 있다. 중온 범위 히트파이프의 작동유체로서 다우섬-A(Dowtherm-A)는 $150^{\circ}C$이상 $400^{\circ}C$까지의 범위에서 소수에 불과한 선택적 대안 중 하나이다. 따라서 본 연구에서는 용융염을 사용하는 중온 태양열축열조에 적용 가능한 다우섬-A 히트파이프의 성능을 파악하여 기술적 자료를 제시하고자 하였다. 열원으로는 고온 고압의 과열증기, 그리고 열침으로는 중온의 포화증기를 고려하였다. 용융염 축열조를 수직으로 관통하는 히트파이프는 하단부에서 열원 증기와 열교환 가능하며, 중앙부에서 축열물질과 열교환하고, 상단부에서는 중온 증기와 접촉할 수 있도록 배치하였다. 축열모드에서는 히트파이프의 하단부가 증발부로 작동하고, 중앙부가 응축부로 작동하여 용융염으로 열을 방출하면 용융염의 온도가 상승하고 용융점에 도달하면 액상으로의 상변화가 진행되면서 축열이 활성화된다. 축열모드에서 히트파이프의 상단부는 단열부로 작동한다. 방열과정에서는 히트파이프의 하단부가 단열된 상태이고, 중앙부는 용융염으로부터 열을 받아 증발부로 작동하며, 상단부는 중온 증기로 열을 방출하므로 응축부로 작동한다. 즉, 축열시스템의 작동모드에 따라 하나의 히트파이프에서 증발부, 응축부, 단열부의 위치가 변하게 된다. 특히, 히트파이프의 중앙 부분이 응축부에서 증발부로 전환될 때에도 작동이 보장되려면 내부 작동유체의 연속적인 재순환이 가능해야 하므로, 일반 히트파이프에서와는 달리 초기 작동액체의 충전량을 증발부 전체의 체적보다 더 많이 과충전해야 한다. 이러한 히트파이프의 성능 파악을 위한 실험에서 고려한 변수들은 열부하, 작동액체의 충전률, 작동온도 등이며, 열수송 성능의 지표로서는 유효열전도율과 열저항을 이용하였다. 중온범위에서 적정한 작동온도를 성취하기 위해 실험에서는 전압 조절기로 열부하를 조절하는 동시에 항온조로 응축부의 냉각수 입구 온도를 제어하였다. 하나의 히트파이프에 대해서 최대 1 kW까지의 열부하에서 냉각수 입구 온도를 $40^{\circ}C$에서 $80^{\circ}C$ 범위로 변화시키면 히트파이프 작동온도를 약 $250^{\circ}C$ 내외로 조절 가능하였다. 히트파이프 작동액체 충전률은 윅구조물의 공극 체적을 기준으로 372%에서 420%까지 변화 시켰다. 실험 결과를 토대로 열저항과 유효 열전도율을 각각 입력 열유속, 작동온도, 작동액체 충전률 등의 함수로 제시했다. 동일한 냉각수 온도에서는 충전률이 높을수록 히트파이프의 작동온도가 감소하였다. 열저항 값의 범위는 최소 $0.12^{\circ}C/W$에서 최대 $0.15^{\circ}C/W$까지로 나타났으며 유효 열전도율의 값은 최소 $7,703W/m{\cdot}K$에서 최대 $8,890W/m{\cdot}K$까지 변화했다. 최소 열저항은 충전률 420%인 경우에 나타났는데 이때의 작동온도는 약 $262^{\circ}C$이었다. 히트파이프의 작동한계로서 드라이아웃(dry-out)은 충전률 372%의 경우에 열부하 950 W에서 발생하였으나, 그 이상의 충전률에서는 열부하 1060 W까지 작동한계 발생이 관찰되지 않았다. 실험 결과 본 연구에서의 히트파이프는 중온 태양열 축열조에 적용되어 개당 약 1 kW의 열부하를 이송하면서 축열물질 및 축방열 대상 유동매체와 열교환을 하는데 사용하는데 충분할 것이라 판단된다.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.165-179
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• 2005

The object of this study is a development of a stochastic user equilibrium transit assignment algorithm for multiple user classes considering stochastic characteristics and heterogeneous attributes of passengers. The existing transit assignment algorithms have limits to attain realistic results because they assume a characteristic of passengers to be equal. Although one group with transit information and the other group without it have different trip patterns, the past studies could not explain the differences. For overcoming the problems, we use following methods. First, we apply a stochastic transit assignment model to obtain the difference of the perceived travel cost between passengers and apply a multiple user class assignment model to obtain the heterogeneous qualify of groups to get realistic results. Second, we assume that person trips have influence on the travel cost function in the development of model. Third, we use a C-logit model for solving IIA(independence of irrelevant alternatives) problems. According to repetition assigned trips and equivalent path cost have difference by each group and each path. The result comes close to stochastic user equilibrium and converging speed is very fast. The algorithm of this study is expected to make good use of evaluation tools in the transit policies by applying heterogeneous attributes and OD data.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.2
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• pp.43-53
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• 2017

This study aims to analyze the effect of typhoons on pear production. Pears are typical fruits that are vulnerable to typhoon damages, so typhoons are negatively associated with pear productivity. However, relatively less pear damages by typhoons in the main pear production area, comparing to the average in Korea, have been reported. The main production area seems to adopt better agricultural techniques or practices to cope with natural disasters such as typhoons. Thus, this study tests the hypothesis that there are differences of production losses due to typhoons between the main pear production area and the rest using the stochastic frontier analysis. The main production area is defined by Location Quotient Index (LQI), and we found that LQI had a significant effect to decrease the productivity losses in the main production areas, which shows that those production areas alleviated the pear production loss due to typhoons.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.25-41
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• 2011

Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved them more powerful than traditional artificial neural networks (ANNs) (Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al., 2005; Kim, 2003).The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is so cost-sensitive particularly in financial classification problems such as the credit ratings that if the credit ratings are misclassified, a terrible economic loss for investors or financial decision makers may happen. Therefore, it is necessary to convert the outputs of the classifier into wellcalibrated posterior probabilities-based multiclass credit ratings according to the bankruptcy probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create the probabilities (Platt, 1999; Drish, 2001). This paper applied AdaBoost algorithm-based support vector machines (SVMs) into a bankruptcy prediction as a binary classification problem for the IT companies in Korea and then performed the multi-class credit ratings of the companies by making a normal distribution shape of posterior bankruptcy probabilities from the loss functions extracted from the SVMs. Our proposed approach also showed that their methods can minimize the misclassification problems by adjusting the credit grade interval ranges on condition that each credit grade for credit loan borrowers has its own credit risk, i.e. bankruptcy probability.