• Journal of Chest Surgery
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• v.40 no.1 s.270
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• pp.8-16
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• 2007

Background: We performed a prospective clinical study to evaluate the ultrastructural integrity of the myocardium after using Histidine-Tryptophan-Ketoglutarate (HTK) solution in comparison with blood cardioplegic solution during congenital heart surgery. Material and Method: Twenty two patients with acyanotic heart disease, who were scheduled for elective open heart surgery, were randomized into two groups. The HTK Group (n=11) received HTK cardioplegic solution; the blood group (n=11) received conventional blood cardioplegic solution during surgery. The preoperative diagnoses included ventricular septal defect (n=9) and atrial septal defect (n=2) in each group. A small biopsy specimen was taken from the right ventricle's myocardium, and this was processed for ultrastructural examination at the end of 30 minutes of reperfusion. Semiquantitative electron microscopy was carried out 'blindly' in 4 areas per specimen and in 5 test fields per area by 'random systematic sampling' and 'point and intersection counting'. The morphology of the mitochondrial membrane and cristae were then scored. The interstitial edema of the myocardium was also graded. Result: The semiquantitative score of the mitochondrial morphology was $19.65{\pm}4.75$ in the blood group and $25.25{\pm}5.85$ in the HTK group (p=0.03). 6 patients (54.5%) in the blood group and 3 patients (27.3%) in the HTK group were grade 3 or more for the interstitial edema of the myocardium. Conclusion: The ultrastructural integrity was preserved even better with HTK solution than with conventional blood cardioplegic solution.

• Land and Housing Review
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• v.2 no.4
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• pp.453-461
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• 2011

This study is to derive a project model based on potential demand for Korean-style houses, focusing on new town detached housing sites that LH supplies and to test validity of the derived model and to present the direction and supply methods of the projects. The existing high-class new town Korean-style housing developments that have been considered were found to have little business value due to problems in choice of location and discordance of demand, so 6 types of projects were established through the methods of changes in planned scale, combined use, and subdivision of plot of land based on the results of survey. The type that has the highest business value among the project models was block-type multifamily houses, and this can be interpreted as the increase in total construction area leading to increase inrevenues of allotment sales due to economies of scale. The feasibility of mass housing model in which small-scale Korean-style houses are combined with amenities was found to be high, and if the same project conditions as those of the block-type multifamily houses are applied, the business value of the Korean-style tenement houses was found to be high. Besides, the high-class housing models within block-type detached housing areas are typical projects that the private sector generally promotes, and the construction cost was found to be most expensive with 910 million won per house. In order to enhance the business value of the Korean-style housing development, collectivization such as choice of location, diversification of demand classes, optimization of house sizes, and combination of uses is needed. And in order to adopt Korean-style houses in the detached housing sites, the adjustments and division of the existing planned plots are needed, and the strategies to cope with new demand through supplying Korean-style housing types of sites can be suggested. Also breaking away from the existing uniform residential development methods, the development method through supplying original land that is natural land not yet developed besides basic infrastructures (main roads and water and sewage) can be considered, and as the construction of more than 1~2 stories building is impossible due to the structure of Korean-style house roof and furniture. So it can be suggested that original land in the form of hilly land is considered to be most suitable to large-scale development projects.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.189-194
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• 2008

Middle-infrared (MIR) spectral region between 3.0 and $5.0\;{\mu}m$ in wavelength is useful for observing high temperature events such as volcanic activities and forest fire. However, atmospheric effects and sun irradiance in day time has not been well studied for this MIR spectral band. The objectives of this basic study is to evaluate atmospheric effects and eventually to estimate surface temperature from a single channel MIR image, although a typical approach utilize split-window method using more than two channels. Several parameters are involved for the correction including various atmospheric data and sun-irradiance at the area of interest. To evaluate the effect of sun irradiance, MODIS MIR images acquired in day and night times were used for comparison. Atmospheric parameters were modeled by MODTRAN, and applied to a radiative transfer model for estimating the sea surface temperature. MODIS Sea Surface Temperature algorithm based upon multi-channel observation was performed in comparison with results from the radiative transfer model from a single channel. Temperature difference of the two methods was $0.89{\pm}0.54^{\circ}C$ and $1.25{\pm}0.41^{\circ}C$ from the day-time and night-time images, respectively. It is also shown that the emissivity effect has by more largely influenced on the estimated temperature than atmospheric effects. Although the test results encourage using a single channel MR observation, it must be noted that the results were obtained from water body not from land surface. Because emissivity greatly varies on land, it is very difficult to retrieval land surface temperature from a single channel MIR data.

• Journal of Korea Port Economic Association
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• v.37 no.1
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• pp.31-70
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• 2021

The purpose of this paper is to measure the clustering change and analyze empirical results, and choose the clustering ports for Busan, Incheon, and Gwangyang ports by using Hierarchical clustering(single, complete, average, and centroid), Silhouette, and 2SCE[the Second Stage(Type II) cross-efficiency] matrix clustering models on Asian container ports over the period 2009-2018. The models have chosen number of cranes, depth, birth length, and total area as inputs and container TEU as output. The main empirical results are as follows. First, ranking order according to the efficiency increasing ratio during the 10 years analysis shows Silhouette(0.4052 up), Hierarchical clustering(0.3097 up), and 2SCE(0.1057 up). Second, according to empirical verification of the Silhouette and 2SCE models, 3 Korean ports should be clustered with ports like Busan Port[ Dubai, Hong Kong, and Tanjung Priok], and Incheon Port and Gwangyang Port are required to cluster with most ports. Third, in terms of the ASEAN, it would be good to cluster like Busan (Singapore), Incheon Port (Tanjung Priok, Tanjung Perak, Manila, Tanjung Pelpas, Leam Chanbang, and Bangkok), and Gwangyang Port(Tanjung Priok, Tanjung Perak, Port Kang, Tanjung Pelpas, Leam Chanbang, and Bangkok). Third, Wilcoxon's signed-ranks test of models shows that all P values are significant at an average level of 0.852. It means that the average efficiency figures and ranking orders of the models are matched each other. The policy implication is that port policy makers and port operation managers should select benchmarking ports by introducing the models used in this study into the clustering of ports, compare and analyze the port development and operation plans of their ports, and introduce and implement the parts which required benchmarking quickly.

• Journal of the Korea Organic Resources Recycling Association
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• v.27 no.2
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• pp.31-40
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• 2019

In Korea, 51,013 thousand tons of livestock manure was generated in 2018. A total of 46,530 thousand tons, which is 91.2% of the total amount of livestock manure generated, was treated by composting(40,647 thousand tons) or liquid fertilization(5,884 thousand tons) method. At present, the policy of livestock manure treatment in Korea is to make livestock manure into organic fertilizer(compost, liquid fertilizer) and then to applicate it on agricultural land. And this policy is very effective in terms of livestock manure treatment and nutrient recycling. However, considering the steadily declining farmland area for decades, the use of livestock manure compost could be limited in the future. There is also concern that local nutrient overloading, nutrient management regulation, and restrictions on the number of livestock may become serious problem for livestock manure treatment. In addition, there are some opinions that nutrient derived from livestock manure may flow into tributaries of major dams. In recent years, there has been a suspicion that fine dust may be generated from livestock manure compost. In recent years, the use of livestock manure fertilizer has been rapidly increasing, there is a growing demand of the development of new technologies for livestock manure treatment. Especially, cow excretes a larger amount of manure than other livestock, so that the efficiency of development of new technology for cow manure treatment will be high. Therefore, in this study, the combustion characteristics of cow manure pellet were investigated in order to analyzed whether cow manure could be used as source of solid fuel. During the combustion test, the weight loss of the cow manure pellet began to increase when the temperature of the combustion chamber reached $300^{\circ}C$. The ratio of $H_2$, $CH_4$, CO in the pyrolysis gas produced in the pyrolysis process of cow manure pellet were 6.65~11.62%, 0.58~1.54 and 11.47~14.07%, respectively.

• International Area Studies Review
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• v.21 no.4
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• pp.41-63
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• 2017

FDI can either be absorbed in the production cycle with domestic investment and create an inducement effect or it can remain as an exogenous factor and increase the volatility of GDP. The purpose of this paper is to research these different impacts that FDI could have. For that, the endogenous growth theory was employed. The statistic method used are the panel model for sectoral analysis, and GARCH model and VAR for time series analysis. Myanmar was selected as this paper's research subject because it is one of countries which had a colossal amount of FDI inflow recently. The panel analysis did not confirm the causality between sectoral FDI and sectoral GDP. The reason for this could be in the lack of data, since sectoral data exists yearly only during 2006-2016. Therefore this study conducted the times series analysis. According to the results, during 2006 until 2010, it showed signs of GARCH but the effect of FDI on GDP was nonexistent, which means FDI was not integrated into the domestic production cycle but stayed in residual terms. During 2011 to 2016, FDI seemed to affect the growth of Myanmar's GDP. The estimation confirmed the existence of GARCH and the Granzer causality test confirmed that FDI influenced the GARCH, which signified FDI increased the volatility of GDP. The VAR analysis showed responses of GDP to FDI was small(about 0.0007). This research assumes that FDI can be divided in two parts: one part which can be assimilated in the domestic production cycle and the other where it stays outside of the production cycle. The former creates production inducement effect and the latter only increases the volatility of GDP. According to this study, the latter outweighs the former impact in Myanmar.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.13-29
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• 2021

The purpose of this study was to analyze the spatial distribution and location factors of startups by generation (young and middle-aged) in Seoul. To this end, a research model was established that included factors of industry, population, and startup institutions by generation in 424 administrative districts using the Seoul Business Enterprise Survey(2018), which includes data on the age group of entrepreneurs. As an analysis method, descriptive statistics were conducted to confirm the frequency, average and standard deviation of startups by generation and major variables in the administrative districts of Seoul, and spatial distribution and characteristics of startups by generation were analyzed through global and local spatial autocorrelation analysis. In particular, the spatial distribution of startups in Seoul was confirmed in-depth by categorizing and analyzing startups by major industries. Afterwards, an appropriate spatial regression analysis model was selected through the Lagrange test, and based on this, the location factors affecting startups by generation were analyzed. The main results derived from the research results are as follows. First, there was a significant difference in the spatial distribution of young and middle-aged startups. The young people started to startups in the belt-shaped area that connects Seocho·Gangnam-Yongsan-Mapo-Gangseo, while middle-aged people were relatively active in the southeastern region represented by Seocho, Gangnam, Songpa, and Gangdong. Second, startups by generation in Seoul showed various spatial distributions according to the type of business. In the knowledge high-tech industries(ICT, professional services) in common, Seocho, Gangnam, Mapo, Guro, and Geumcheon were the centers, and the manufacturing industry was focused on existing clusters. On the other hand, in the case of the life service industry, young people were active in startups near universities and cultural centers, while middle-aged people were concentrated on new towns. Third, there was a difference in factors that influenced the startup location of each generation in Seoul. For young people, high-tech industries, universities, cultural capital, and densely populated areas were significant factors for startup, and for middle-aged people, professional service areas, low average age, and the level of concentration of start-up support institutions had a significant influence on startup. Also, these location factors had different influences for each industry. The implications suggested through the study are as follows. First, it is necessary to support systematic startups considering the characteristics of each region, industry, and generation in Seoul. As there are significant differences in startup regions and industries by generation, it is necessary to strengthen a customized startup support system that takes into account these regional and industrial characteristics. Second, in terms of research methods, a follow-up study is needed that comprehensively considers culture and finance at the large districts(Gu) level through data accumulation.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1353-1369
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• 2023

In the event of a disaster accident at sea, the scale of damage will vary due to weather effects such as wind, currents, and tidal waves, and it is obligatory to minimize the scale of damage by establishing appropriate control plans through quick on-site identification. In particular, it is difficult to identify pollutants that exist in a thin film at sea surface due to their relatively low viscosity and surface tension among pollutants discharged into the sea. Therefore, this study aims to develop an algorithm to detect suspended pollutants on the sea surface in RGB images using imaging equipment that can be easily used in the field, and to evaluate the performance of the algorithm using input data obtained from actual waters. The developed algorithm uses image enhancement techniques to improve the contrast between the intensity values of pollutants and general sea surfaces, and through histogram analysis, the background threshold is found,suspended solids other than pollutants are removed, and finally pollutants are classified. In this study, a real sea test using substitute materials was performed to evaluate the performance of the developed algorithm, and most of the suspended marine pollutants were detected, but the false detection area occurred in places with strong waves. However, the detection results are about three times better than the detection method using a single threshold in the existing algorithm. Through the results of this R&D, it is expected to be useful for on-site control response activities by detecting suspended marine pollutants that were difficult to identify with the naked eye at existing sites.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.1
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• pp.77-81
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• 2009

Purpose: The PET of the PET/CT (Positron Emission Tomography/Computed Tomography) quantitatively shows the biological and chemical information of the body, but has limitation of presenting the clear anatomic structure. Thus combining the PET with CT, it is not only possible to offer the higher resolution but also effectively shorten the scanning time and reduce the noises by using CT data in attenuation correction. And because, at the CT scanning, the contrast media makes it easy to determine a exact range of the lesion and distinguish the normal organs, there is a certain increase in the use of it. However, in the case of using the contrast media, it affects semi-quantitative measures of the PET/CT images. In this study, therefore, we will be to establish the reliability of the SUV (Standardized Uptake Value) with CT data correction so that it can help more accurate diagnosis. Materials and Methods: In this experiment, a total of 30 people are targeted - age range: from 27 to 72, average age : 49.6 - and DSTe (General Electric Healthcare, Milwaukee, MI, USA) is used for equipment. $^{18}F$- FDG 370~555 MBq is injected into the subjects depending on their weight and, after about 60 minutes of their stable position, a whole-body scan is taken. The CT scan is set to 140 kV and 210 mA, and the injected amount of the contrast media is 2 cc per 1 kg of the patients' weight. With the raw data from the scan, we obtain a image showing the effect of the contrast media through the attenuation correction by both of the corrected and uncorrected CT data. Then we mark out ROI (Region of Interest) in each area to measure SUV and analyze the difference. Results: According to the analysis, the SUV is decreased in the liver and heart which have more bloodstream than the others, because of the contrast media correction. On the other hand, there is no difference in the lungs. Conclusions: Whereas the CT scan images with the contrast media from the PET/CT increase the contrast of the targeted region for the test so that it can improve efficiency of diagnosis, there occurred an increase of SUV, a semi-quantitative analytical method. In this research, we measure the variation of SUV through the correction of the influence of contrast media and compare the differences. As we revise the SUV which is increasing in the image with attenuation correction by using contrast media, we can expect anatomical images of high-resolution. Furthermore, it is considered that through this trusted semi-quantitative method, it will definitely enhance the diagnostic value.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.137-148
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• 2014

Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used