• Applied Chemistry for Engineering
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• v.22 no.4
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• pp.405-410
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• 2011

High-performance of an electric double layer capacitance (EDLC) electrode was prepared by the amino-fluorination of activated carbon by using $NF_3$ gas. The pore structure and surface chemistry were investigated based on the specific capacitance of EDLC. The amino-fluorination of activated carbon introduced functional groups of nitrogen and fluorine which are beneficial for the specific capacitance of EDLC without the change of pore structures. The E-NF100AC electrode, which has nitrogen and fluorine functional groups less than 1 at%, showed the highly improved specific capacitance of 528 (${\pm}9$) F/g at 2 mV/s showing 122% improved value when comparing with that of non-functionalized E-RAC electrodes. Whereas, the E-NF200AC electrode, which has nitrogen and fluorine functional groups over 1 at%, showed the decreased specific capacitance because of perfluorinated introduction. So, it is concluded that the proper contents of nitrogen and fluorine groups improved the specific capacitance of EDLC.

• Kosin Medical Journal
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• v.33 no.2
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• pp.181-190
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• 2018

Objectives: Our school introduced a new curriculum based on faculty-directed, intensive, small-group teaching of clinical skills in the third-year medical students. To examine its effects, we compared the mean scores on an OSCE between the third- and fourth-year medical students. Methods: Third- and fourth-year students did rotations at the same five OSCE stations. They then completed a brief self-reporting questionnaire survey to examine the degree of satisfaction with new curriculum in the third-year students and clinical practice in the fourth-year students, as well as their perception of confidence and preparedness. We analyzed the OSCE data obtained from 158 students, 133 of whom also completed the questionnaire. Results: Mean OSCE scores on the breast examination and wet smear stations were significantly higher in the third-year group (P < 0.001). But mean OSCE scores of motor-sensory examination and lumbar puncture were significantly higher in the fourth-year group (P < 0.05). The mean OSCE scores had no significant correlation with satisfaction. In addition, the self-ratings of confidence had a high degree of correlation with satisfaction with new curriculum (r = 0.673) and clinical practice (r = 0.692). Furthermore, there was a moderate degree of correlation between satisfaction and preparedness in both groups (r = 0.403 and 0.449). Conclusions: There is no significant difference in the effect on the degree of clinical performance and confidence between an intensive-small group teaching and a 1-year clinical practice. If combined, intensive small group teaching and clinical practice would be useful to improve the degree of ability and confidence in medical students.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.19-30
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• 2018

Visual information understanding is known as one of the most difficult and challenging problems in the realization of machine intelligence. This paper proposes deriving visual verb and construction of ActionNet database as a video database for video semantic understanding. Even though development AI (artificial intelligence) algorithms have contributed to the large part of modern advances in AI technologies, huge amount of database for algorithm development and test plays a great role as well. As the performance of object recognition algorithms in still images are surpassing human's ability, research interests shifting to semantic understanding of video contents. This paper proposes candidates of visual verb requiring in the construction of ActionNet as a learning and test database for video understanding. In order to this, we first investigate verb taxonomy in linguistics, and then propose candidates of visual verb from video description database and frequency of verbs. Based on the derived visual verb candidates, we have defined and constructed ActionNet schema and database. According to expanding usability of ActionNet database on open environment, we expect to contribute in the development of video understanding technologies.

• New Physics: Sae Mulli
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• v.68 no.11
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• pp.1192-1195
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• 2018

We studied the electrical properties of organic thin-film transistors (OTFTs) fabricated at different deposition rates by measuring the field-effect mobility and the threshold voltages. As the active layer, pentacene thin film with a thickness of 50 nm was deposited at a rate of $0.05{\AA}/s$ to $1.14{\AA}/s$. The thickness of the drain-source gold electrode was 50 nm. The mobility was $1.9{\times}10^{-1}cm^2/V{\cdot}s$ at a deposition rate of $0.05{\AA}/s$, the mobility increased to $5.2{\times}10^{-1}cm^2/V{\cdot}s$ when the deposition rate was increased to $0.4{\AA}/s$, and then the mobility decreased to $6.5{\times}10^{-1}cm^2/V{\cdot}s$ when the deposition rate decreased to $1.14{\AA}/s$. Thus, the mobility of pentacene OTFTs was observed to depend on the thermal deposition rate.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.4
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• pp.63-70
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• 2003

In the modern electronic world, the authentication of a person is an important task in many areas of online-transactions. Using biometrics to authenticate a person's identity has several advantages over the present practices of Personal Identification Numbers(PINs) and passwords. To gain maximum security in the verification system using biometrics, the computation of the verification as well as the store of the biometric pattern has to be taken place in the security token(smart card, USB token). However, there is an open issue of integrating biometrics into the security token because of its limited resources(memory space, processing power). In this paper, we describe our implementation of the USB security token system having 206MHz StrongARM CPU, 16MBytes flash memory, and 1MBytes RAM. Also, we evaluate the performance of a light-weighted In-gerprint verification algorithm that can be executed in the restricted environments. Based on experimental results, we confirmed that the RAM requirement of the proposed algorithm was about 6.8 KBytes and the Equal Error Rate(EER) was 1.7%.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.5
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• pp.59-69
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• 2011

Since power analysis attack which uses a characteristic that power consumed by crypto device depends on processed data has been proposed, many logics that can block these correlation originally have been developed. DRP logic has been adopted by most of logics maintains power consumption balanced and reduces correlation between processed data and power consumption. However, semi-custom design is necessary because recently design circuits become more complex than before. This design method causes unbalanced design pattern that makes DRP logic consumes unbalanced power consumption which is vulnerable to power analysis attack. In this paper, we have developed new logic style which adds another discharge phase to discharge two output nodes at the same time based on DyCML to remove this unbalanced power consumption. Also, we simulated 1bit fulladder to compare proposed logic with other logics to prove improved performance. As a result, proposed logic is improved NED and NSD to 60% and power consumption reduces about 55% than any other logics.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.135-141
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• 2011

Recent advances in mobile devices and development of various mobile applications dealing with private information of users made user authentication in mobile devices a very important issue. This paper presents a new user authentication method based on touch screen interfaces. This method uses for authentication the PIN digits as well as the exact locations the user touches to input these digits. Our method is fully compatible with the regular PIN entry method which uses numeric keypads, and it provides better usability than the behavioral biometric schemes because its PIN registration process is much simpler. According to our experiments, our method guarantees EERs of 12.8%, 8.3%, and 9.3% for 4-digit PINs, 6-digit PINs, and 11-digit cell phone numbers, respectively, under the extremely conservative assumption that all users have the same PIN digits and cell phone numbers. Thus we can guarantee much higher performance in identification functionality by applying this result to a more practical situation where every user uses distinct PIN and sell phone number. Finally, our method is far more secure than the regular PIN entry method, which is verified by our experiments where attackers are required to recover a PIN after observing the PIN entry processes of the regular PIN and our method under the same level of security parameters.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.58-73
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• 2020

The purpose of this study is to empirically analyze the relationship between organizational commitment, job satisfaction, education and training, human resource development, and communication in Korea's financial industry. In particular, the mediating relationships between organizational commitment and job satisfaction, education and training, human resource development, and communication were examined in order to provide a better understanding of organizational commitment. A structural equation model was used for the empirical analysis of this study. As a result of the study, it was confirmed that education and training, human resource development, communication, organizational commitment, and job satisfaction are correlated within the Korean financial industry. Furthermore, organizational commitment was found to have mediating effects on education and training, human resource development, communication, and job satisfaction. Based on these results, this study emphasizes the importance of education and training for organizational commitment in the Korean financial industry. In particular, this study establishes the importance of a culture of trust within organizations through human resource development programs, communication for job satisfaction, and organizational performance to face changes in the post-COVID era. In the future, more in-depth qualitative studies are required to derive factors related to the employees of financial companies and to conduct comparison analyses with companies in other industries.

• Journal of the Korean Society of Radiology
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• v.15 no.3
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• pp.301-306
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• 2021

The use of tin filters as a way to reduce the medical radiation in computed tomography (CT). However, due to the changed X-ray spectrum with the use of tin filters, disease diagnosis could be affected because it appears as images of different impressions from previous images. Therefore, this study evaluates the changes in images when using tin filter and high pitch in chest low-dose CT. In this study, images were acquired in groups of three for comparison. Group 1 did not apply to tin filter, and used the existing pitch 0.8. Group 2 used a tin filter, pitch 0.8, Group 3 used a tin filter, and pitch 2.5. To compare the image quality, the natural image quality evaluator (NIQE) and the blind/referenceless image quality evaluator (BRISQUE) were used among the blind quality evaluation factors depended on a no-reference basis. As a result, the NIQE values were low in the order of Group 1, Group 3, and Group 2. BRISQUE values were low in the order of Group 3, Group 2 and Group 1. This study confirms the superiority of images of tin filter and high pitch techniques in chest low-dose CT, which is considered to be a fundamental study for acquiring accurate images of patients with difficult breathing control.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.309-327
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• 2021

Dynamic treatment regimes (DTRs) are decision-making rules designed to provide personalized treatment to individuals in multi-stage randomized trials. Unlike classical methods, in which all individuals are prescribed the same type of treatment, DTRs prescribe patient-tailored treatments which take into account individual characteristics that may change over time. The Q-learning method, one of regression-based algorithms to figure out optimal treatment rules, becomes more popular as it can be easily implemented. However, the performance of the Q-learning algorithm heavily relies on the correct specification of the Q-function for response, especially in observational studies. In this article, we examine a number of double-robust weighted least-squares estimating methods for Q-learning in high-dimensional settings, where treatment models for propensity score and penalization for sparse estimation are also investigated. We further consider flexible ensemble machine learning methods for the treatment model to achieve double-robustness, so that optimal decision rule can be correctly estimated as long as at least one of the outcome model or treatment model is correct. Extensive simulation studies show that the proposed methods work well with practical sample sizes. The practical utility of the proposed methods is proven with real data example.