• Journal of the Korean Geographical Society
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• v.50 no.6
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• pp.717-734
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• 2015

The Toyo Bunko (東洋文庫) in Tokyo, Japan is one of the largest library that holds the Korean old geographical documents. About 200 topographies of counties and prefectures, including Giinhansangnyang 杞人間商量 which recorded compilation and improvement plan of the geographical annals belong to it. Several maps and geographical annals of Joseon Period possessed in the Toyo Bunko are set high values on geography since the materials are only belong to it and have not yet been found in Korea. There are very important map collections including six copies of Daedongyeojido 大東輿地圖(1861, 1864) by Kim Jeongho(金正浩) and Suseonjeondo 首善全圖 by Kim, Jungho, collectible stamp of Maema Kyosaku(前間恭作) is imprinted on it, and Gangyeokjundo 疆域全圖 and Dongyeodo 東輿圖 which made with 20-ri and 10-ri grid, owned by Sidehara Daira(幣原坦). Especially Gwanbukjido 關北地圖 which is the northern border map recorded the Lee Sam's(李森) preface who served as a military official of Hamgyeong and Pyeongan Province in early 18th century. These maps and some other maps have a historical value to supplement of the history of Korean Cartography.

• Environmental and Resource Economics Review
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• v.28 no.4
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• pp.527-556
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• 2019

In Korea, nearly 100 billion won is spent annually under the name of energy voucher on 600,000 households for the last five years, and this is a unique case and hard to monitor worldwide. Therefore, no studies have been conducted to assess impacts of the energy voucher on energy consumption and cost burden alleviation for beneficiaries. This paper aims to demonstrate the effectiveness of energy vouchers in terms of energy expense. The propensity score matching was conducted on samples of low-income households based on the Korea Welfare Panel. Then, simple Difference-In-Differences and Fixed-Effect Difference-In-Differences models were applied to estimate the effect of energy vouchers. In results, the beneficiaries of energy vouchers would spend an additional 4,371~4,870 won per month on energy consumption. The ratio is equivalent to 51.9~57.7 percent of the aid, which is also the highest when compared with 23~56 percent of U.S. Food Stamp. In terms of energy welfare, voucher payment could become one of the best management practices. However, identifying the blind spots as non-reciprocal households and expanding the differential support mechanism that reflects the energy consumption environment should be solved in the future.

• Korean Security Journal
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• no.29
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• pp.279-300
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• 2011

Countries recognize seriousness and concern about aviation terrorism, try to stamp out of it but aviation terrorism has been increasing in the world. Airport security is completely up to the result of security screening for passengers, check-in baggages and cargo at the check point. To complete effectively human and physical screening at the airport, it is essential to secure modernized screening equipment and specialized security screener, and airport security supervisor to supervising them. In this study, A survey conducted to find out the effect on screening equipment operating factors of airport security supervisor's individual attitude. The results of the study are as follow First, the duty view of airport security supervisor meaningfully affect expertise of screening equipment operating factors, satisfaction, reliability, and education and training, national point of view meaningfullly doesn't affect screening equipment operating factors. Second, the working condition effects on the education and training, if the working condition is getting better, intent to change occupation is getting lower. Third, duty stress meaningfully effects on the intent to change occupation, now airport security supervisor works in poor condition. Therefore, airport security supervisor needs to be prude of protecting the airport from the terrorism and various attacks and various kinds of aviation security regulations and procedures and comply with operating standards and keep the life of the country and its people, and needs to change awareness. And It is nessasary for government or airport authority or airline to prepare countermeasure for the improvement of their labor conditions.

• Therapeutic Science for Rehabilitation
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• v.8 no.4
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• pp.65-76
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• 2019

Objective : This study aimed to verify the validity and reliability of the Upper Extremity Performance Test for the Elderly (TEMPA) by modifying its items to exhibit cultural differences. Methods : This study included 171 healthy adults and older adults and 41 individuals with impaired upper extremity function. Content validity, discriminant validity, test-retest reliability, and inter-rater reliability were analyzed. Results : The following items, exhibiting cultural differences, were modified: "open a lock and take the top off a pillbox" and "write and affix a postage stamp." The discriminant validity results indicated that participants with normal upper extremity function performed better than those with impaired in the upper extremity function (p<.001). The test-retest reliability of the execution speed (intraclass correlation coefficient; ICC) was .71-.94, functional rating (kappa) was 1.0, and task analysis (ICC) was 1.0. The inter-rater reliability of the speed of execution was 1.0, functional rating was .79-1.0, and task analysis was .94-1.0. Conclusion : TEMPA has moderate to high level of reliability and is an assessment tool that can clearly distinguish individuals with upper extremity impairment from those without impairment.

• Journal of Science and Technology Studies
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• v.18 no.3
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• pp.217-255
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• 2018

Bitcoin, which appeared in 2008, was merely a conceptual virtual currency, but it now enjoys the status as actual money. Bitcoin is an electronic money system that can be traded directly without a central trust institution. Thanks to the popularization of Bitcoin, blockchain technology has become a widespread concern. That technology is expanding not only the currency mechanism, but also a variety of other services. The possibility of a blockchain in relation to actual currency is ongoing. This paper investigates the technological characteristics and social construction of the blockchain by comparing the cases of Bitcoin, Namecoin, and MediBloc among blockchain applications. Namecoin emerged in 2013 is an attempt to replace the centralized Internet Domain Name System(DNS). There has been controversy over that current system for a long time, but replacing the already established system is not easy. Nevertheless, Namecoin has potential as an alternative. Meanwhile, MediBloc is an application that involves distributed management of medical data in South Korea. MediBloc claims that the key producers of medical data are patients themselves. This is to challenge to the question who is a knowledge producer of medical data. Through these three cases, it has discussed that blockchain technology does supports to form more democratic decision-making or simply provide a technical solution as automation. As a citizen, we can intervene in the realization of blockchains by presenting social agenda. This will be a method of the social construction of technology.

• Parasites, Hosts and Diseases
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• v.27 no.2
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• pp.101-108
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• 1989

This study was performed to observe the role of Pneumocystis carinii as an etiologic agent of interstitial pneumonia in immunocompromised hosts. Total 90 male Sprague-Dawley rats, approxi. mately 150-180 g, were used. Fifteen of them were used as control group and remaining 75 (5 groups) were as immunosuppression groups; group 1 received prednisolone (25 mg/kg twice weekly) only; group 2 Prednisolone and tetracycline (75 mk/kg/day) ; group 3 Prednisolone, tetracycline and trimethoprim-sulfamethoxasole (50~250 mg/kg/day) : group 4 prednisolone and trimethoprim-sulfamethoxasole; and group 5 prednisolone and griseofulvin (300 mg/kg/day) until death. The survival days of each group rat were calculated, and upon death their lungs were removed immediately and then stamp smears were prepared and stained by Giemsa or toluidine blue O. For histopathologic observation, lungs were fixed in 10% formalin, cut into sections and stained with Gomori's methenamine silvei, hematoxylin-rosin, and Brovkn & Brenn stain. The results obtained were as follows: 1. The mean survival time of each group rat was 19.3$\pm$5.2 days (group 1), 41.1$\pm$14.0 days (group 2), 50.5$\pm$18.4 days (group 3), 43.0$\pm$22.9 days (group 4) or 21.8$\pm$5.1 days (group 5). Significant differences were noted between group 1 and group 2(p<0.01), group 1 and group 3 (p<0.01), and group 1 and group 4 (p<0.01), which represented bacterial infections were most fatal in immunocompromised rats. Group 5 revealed no difference in the survival day from group 1, while significant differences were noted between group 2 and group 5(P<0.01), group 3 and group 5(p<0.01), and group 4 and group 5(p<0, 01), which represented little importance of fungal infection as the cause of death of the rats. 2. The first fatality due to p. carinii pneumonia occurred 17 days after the beginning of the immunosuppression. The occurrence rate of P. carinii pneumonia in the decreasing order was 92.9% (group 3), 80.0% (group 2 and group 5), 78.6% (group 4) and 33.3% (group 1). With regard to the pathological stage of P. carinii pneumonia, the stage 1 was 11.3%, the stage 2, 28.3%, and the stage 3, 60.4%. 3. Viewing from the duration of immunosuppression, bacterial pneumonia chieay appeared in 1 month, mixed infections (P. carinii and bacteria, or p. carinii and fungi) in 1~2 months, and pure P. carinii pneumonia after 2 months. The present study revealed that P. carinii pneumonia was the most important cause of death of immunocompromised rats later than 1 month after the start of immunosuppression.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.