• Journal of Service Research and Studies
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• v.11 no.4
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• pp.43-55
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• 2021

This study analyzed the efficiency of medical services in OECD member countries by dividing it into operational efficiency and quality efficiency. For this purpose, data from 2017-2019 OECD Health Statistics were used. As the analysis method, super efficiency was measured by applying an output-oriented Variable Returns to Scale (VRS) model. As a result of the analysis, Switzerland, Korea, and Italy were included in the high group of operational efficiency, Canada, Greece, Denmark, etc. in the medium group, and Belgium, Germany, and Spain in the low group. Based on quality efficiency, Norway, Switzerland, and Spain are in the high group, and Greece, Denmark, Mexico, etc. are in the medium group, and the Netherlands, Germany, Belgium, etc. were included in the low group. As a result of comparative analysis of efficiency by OECD member countries as of 2018, it was found that Korea's operational efficiency was the most efficient and quality efficiency was inefficient. Korea (0.998) should improve life expectancy by 0.2 (0.2%) and subjective health perception by 44.2 (138.1%) by benchmarking Greece (0.422), Switzerland (0.207), and Spain (0.371) to improve quality efficiency. Unlike most previous studies that focused on operational efficiency, this study measured quality efficiency together and analyzed the efficiency of the medical service industry in each OECD member country. Through this, this study has implications in that it confirmed the international competitiveness of the domestic medical service industry and suggested ways to improve efficiency.

• Journal of the Korean Society of Radiology
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• v.11 no.5
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• pp.361-370
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• 2017

In the Brain MRI, RF Pulse is irradiated on the human body in order to acquire an image. At this time, a considerable part of the irradiated RF Pulse energy is absorbed as it is in our body. This will raise the temperature of the human body, but depending on the extent of exposure, it will affect the human body. The change of the SAR and the temperature of the head according to the change of the magnetic field strength is examined. And to investigate the difference in results depending on the use of dental implant. In the human head model, 64 MHz RF Pulse frequency generated from 1.5 T, 128 MHz RF Pulse frequency generated from 3.0 T, and 298 MHz RF Pulse frequency generated from 7.0 T send a frequency and experiment was performed using dental implant using the XFDTD program, we measured the SAR and body temperature changes around the head. The SAR value showed up to about 5800 times the difference at the RF Pulse frequency of 256 MHz, when with dental implant than without dental implant and as the frequency increased, the use of the dental implant increased difference in the SAR value. The change of the temperature of the head showed a temperature rise nearly 2 to 4 times when with dental implant than without dental implant. As the RF Pulse frequency increase, the SAR value increase, but the change of the temperature of the head decrease. Because of as the frequency increase, wavelength is smaller and the more the amount absorbed by the surface of the human. Physiological and biochemical studies of the human body ar necessary through studies of the presence of dental implant and the cause of reaction caused by change in the RF Pulse frequency.

• Journal of the Korean Society of Radiology
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• v.12 no.4
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• pp.481-489
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• 2018

In MRI examination, when irradiating the human body with RF Pulse to acquire images, the portion of the irradiated RF Pulse energy is absorded into the human body, and this will affect the temperature of the human body. If a metal is inserted into the human body even if the same RF Pulse energy is applied, the SAR value increases and the body temperature changes due to the increase in the electromagnetic wave conductivity of the metal. So we measure and compared with the change in the SAR and temperature in the implant material of the dental implant in Brain MRI examinations. Experiments were performed on a human head model using a 64MHz and 128 MHz RF Pulse frequency generated by a 3.0 Tesla MRI apparatus. And then changed material of dental implants to Titanium and $Al_2O_3$. Using the XFDTD program, the changes in SAR and body temperature around the head were examined. When with Titanium the SAR value and temperature of Brain increased, but with $Al_2O_3$ showed lower SAR and temperature as compared with Titanium. The dental implants were low in SAR and temperature of the head in $Al_2O_3$, which are electrical insulators with low electrical conductivity, compared to Titanium, which is an electrical conductor. It is necessary to study the biologic effect of patient with brain MRI when titanium dental implant material is inserted in the future. Because the maximum value of SAR is much higher than the limit when dental implant material is Titanium. In addition, it is necessary to use an implant of $Al_2O_3$ material to reduce the SAR value and temperature of the Brain in Brain MRI examination.

• 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 Korean Society of Forest Science
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• v.105 no.2
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• pp.247-252
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• 2016

This study was conducted to evaluate the technical efficiency of Annual Chestnut production in South Korea. In this study, technical efficiency is the maximum possible production for which a certain amount of costs is inputted. For analysis on the technical efficiency we used output-oriented BCC Model, and then we analyzed correlation among input costs, production, gross income, net income, and market price per unit in order to determine the cause of variation in the technical efficiency. As study materials, we used statistics for the forestry production costs for 7 years from 2008 to 2014. The study results showed that the maximum possible production and actual production in 2008, 2009, and 2010 were 1,568 kg, 1,745 kg, and 1,534 kg by hectares in the order which were the same values. Consequently, the technical efficiency of those was all evaluated as 1.00. On the other hand, actual production from 2011 to 2014 was 1,270 kg 1,047 kg, 1,258 kg, and 1,488 kg by hectares in the order and the maximum possible production was 1,524 kg, 1,467 kg, 1,635 kg, and 1,637 kg by hectares in the analysis. From those values, the technical efficiency was evaluated in the following order:0.83, 0.71, 0.75, 0.91. The lowest value of the technical efficiency was 0.71 in 2012, and the values of this increased gradually since 2013. It is indicated that the cause of variation in the technical efficiency was related to the relationship between production and market price, and there was a negative correlation with r = -0.821 (p<0.05). The level of maximum available production per unit area was between 1,488kg in lower limit and 1,745 kg in upper limit, and the average was turned out as 1,548 kg.

• Journal of Korea Port Economic Association
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• v.34 no.3
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• pp.17-52
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• 2018

The purpose of this paper is to measure the clustering change and analyze empirical results. Additionally, by using k-means, hierarchical, and mixed models on Asian container ports over the period 2006-2015, the study aims to form a cluster comprising Busan, Incheon, and Gwangyang ports. The models consider the number of cranes, depth, birth length, and total area as inputs and container twenty-foot equivalent units(TEU) as output. Following are the main empirical results. First, ranking order according to the increasing ratio during the 10 years analysis shows that the value for average linkage(AL), mixed ward, rule of thumb(RT)& elbow, ward, and mixed AL are 42.04% up, 35.01% up, 30.47%up, and 23.65% up, respectively. Second, according to the RT and elbow models, the three Korean ports can be clustered with Asian ports in the following manner: Busan Port(Hong Kong, Guangzhou, Qingdao, and Singapore), Incheon Port(Tokyo, Nagoya, Osaka, Manila, and Bangkok), and Gwangyang Port(Gungzhou, Ningbo, Qingdao, and Kasiung). Third, optimal clustering numbers are as follows: AL(6), Mixed Ward(5), RT&elbow(4), Ward(5), and Mixed AL(6). Fourth, empirical clustering results match with those of questionnaire-Busan Port(80%), Incheon Port(17%), and Gwangyang Port(50%). The policy implication is that related parties of Korean seaports should introduce port improvement plans like the benchmarking of clustered seaports.