• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.216-227
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• 2020

In science and technology diplomacy, major countries actively utilize their capabilities in science and technology for public diplomacy, especially for promoting diplomatic relations with politically sensitive regions and countries. Recently, with an increase in the influence of science and technology on national development, interest in science and technology diplomacy has increased. So far, science and technology diplomacy has relied on experts to find research topics that are of common interest to both the countries. However, this method has various problems such as the bias arising from the subjective judgment of experts, the attribution of the halo effect to famous researchers, and the use of different criteria for different experts. This paper presents an objective data-based approach to identify and recommend research topics to support science and technology diplomacy without relying on the expert-based approach. The proposed approach is based on big data analysis that uses deep-learning techniques and bibliometric methods. The Scopus database is used to find proper topics for collaborative research between two countries. This approach has been used to support science and technology diplomacy between Korea and Hungary and has raised expectations of policy makers. This paper finally discusses aspects that should be focused on to improve the system in the future.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.73-81
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• 2016

In general, infrared images have less sharpness and image details than visible images. So, the prior image upscaling methods are not effective in the infrared images. In order to solve this problem, this paper proposes an algorithm which initially up-scales an input infrared (IR) image by using adaptive dynamic range encoding (ADRC)-based super-resolution (SR) method, and then fuses the result with the corresponding visible images. The proposed algorithm consists of a up-scaling phase and a fusion phase. First, an input IR image is up-scaled by the proposed ADRC-based SR algorithm. In the dictionary learning stage of this up-scaling phase, so-called 'pre-emphasis' processing is applied to training-purpose high-resolution images, hence better sharpness is achieved. In the following fusion phase, high-frequency information is extracted from the visible image corresponding to the IR image, and it is adaptively weighted according to the complexity of the IR image. Finally, a up-scaled IR image is obtained by adding the processed high-frequency information to the up-scaled IR image. The experimental results show than the proposed algorithm provides better results than the state-of-the-art SR, i.e., anchored neighborhood regression (A+) algorithm. For example, in terms of just noticeable blur (JNB), the proposed algorithm shows higher value by 0.2184 than the A+. Also, the proposed algorithm outperforms the previous works even in terms of subjective visual quality.

• Journal of Korean society of Dental Hygiene
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• v.20 no.1
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• pp.107-116
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• 2020

Objectives: This study applied the co-orientation model to investigate the degree to which dental hygienists and dentists recognize the efficiency of dental hygienists' non-surgical periodontal therapy work; the basic data can be provided as a systematic arrangement that can be applied and extended to dental clinics to raise mutual understanding. Methods: Independent sample t-tests, one-way ANOVA, and paired t-tests were conducted with a total of 888 subjects (530 dental hygienists and 358 dentists) using SPSS Statistics 22.0. Results: The analysis showed that, dental hygienists had higher recognition of the efficiency of their work (p<0.001) than dentists, with respect to all items(p>0.05). With respect to subjective agreement, dental hygienists estimated lower recognition among dentists than other dental hygienists and dentists estimated higher recognition among dentists than dental hygienists. With respect to accuracy, dentists' estimation was lower than the actual recognition among dental hygienists and dental hygienists' estimation was higher than the actual recognition among dentists in all cases except the efficiency of dental hygienists' patient education work and constant learning. Conclusions: There was wide gap between dental hygienists and dentists in recognition of the efficiency of dental hygienists' non-surgical periodontal therapy work. Actions must be taken to raise mutual understanding between dental hygienists and dentists regarding dental hygienists' non-surgical periodontal therapy work, to spread this recognition throughout the dental industry, and to implement systematic support at dental clinics.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.623-637
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• 2016

This study examined the importance of social capital in facilitating older adults' learning and adaptation of information technology as well as alleviating depressive symptoms. At two senior community centers in South Korea, 144 adults aged 60 and older were recruited to participate in 12 week-long technology classes to learn computers, smart phone, and internet skills. At the baseline interviews were conducted to assess their health status, depression, and online social relationships. Online and offline social capital (bonding vs. bridging) was assessed (Williams, 2006). Four-step Hierarchical Linear Regression analysis was conducted to examine the effects of online social relationship on depression. Findings suggested that depressive symptoms were associated with being widowed, being unemployed, and perceiving poor health status. Adding social capital variables in the final step, older adults who perceived less stressors, greater level of subjective health and high online bonding capitals had less depressive symptoms. Only online social bonding was significant in alleviating depression. This final model explained 48% of the variance. Computer/Internet training for older adults need to consider the significant role bonding social capital can play. The findings of this pilot study provided a preliminary base of knowledge about acceptable community-based interventions for older adults.

• Journal of the Korean earth science society
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• v.32 no.1
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• pp.84-98
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• 2011

The study investigated the linguistic characteristics of middle school students' writing on the themes of earth science through analysis of its genre and register. Data for analysis included $7^{th}$ grade and $9^{th}$ grade students' writings about 'global warming' and 'classification of rocks'. The results of this study include: First, many students were not accustomed to writing in genre, especially exposition genre. Second, in terms of ideational meaning, the material verbs representing action or doing were more dominant than relational verbs that are related to the attribute or definition of things, and additional logical relations were predominant. Third, regarding interpersonal meaning, agents, emotions, subjective opinions appeared in the writings and students did not express their ideas conclusively and revealed feelings of doubt and uncertainty about their knowledge. Fourth, as for textual meaning, most students listed fragments of information using additional conjunctions in simple structures and were not accustomed to writing texts with organizing structures, logical patterns, cohesion, and coherence. From these results, we argued that the scientific writings should be emphasized in science learning that aims to foster scientific literacy. In addition, we discussed the necessity of improving science teachers' perceptions on scientific writing as well as setting up a specific plan in the national curriculum.

• The Journal of Society for e-Business Studies
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• v.25 no.1
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• pp.13-33
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• 2020

This study proposes a Korean sentimental analysis algorithm that utilizes a letter-unit embedding and convolutional neural networks. Sentimental analysis is a natural language processing technique for subjective data analysis, such as a person's attitude, opinion, and propensity, as shown in the text. Recently, Korean sentimental analysis research has been steadily increased. However, it has failed to use a general-purpose sentimental dictionary and has built-up and used its own sentimental dictionary in each field. The problem with this phenomenon is that it does not conform to the characteristics of Korean. In this study, we have developed a model for analyzing emotions by producing syllable vectors based on the onset, peak, and coda, excluding morphology analysis during the emotional analysis procedure. As a result, we were able to minimize the problem of word learning and the problem of unregistered words, and the accuracy of the model was 88%. The model is less influenced by the unstructured nature of the input data and allows for polarized classification according to the context of the text. We hope that through this developed model will be easier for non-experts who wish to perform Korean sentimental analysis.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.6 no.3
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• pp.477-492
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• 1999

The disease patterns among the Korean was shifted from acute and infectious diseases to chronic diseases. According to the these disease patterns trends, people have concerned about the health promotion and health behaviors. Pender's(1996) revised health promotion model(HPM) is consist of three categories; Individual characteristics and experiences, Behavior-specific cognitions and affect, behavioral outcome. Of these categories, individual characteristics and experiences, this category of variables is considered to be of biological, psychological and socio-cultural personal factors, especially, individual fatigue. Futhermore. these variables constitute a critical core for nursing intervention, as they are subject to modification through nursing actions. But there is no few the research of the relationship between the fatigue and health promotion. Therefore, the purpose of this study is to investigate the correlation between the fatigue and health promoting life style among a rural college students. Additionally, this descriptive correlational study identified the relation of demographic factors and fatigue, health promoting life style. From June 20 to 26, 1998, a convenience sample of 270 college students completed the questionnaire of the fatigue and health promoting life style profile which were developed by the Yoshitake(1978) and Walker, et al.(1987), respectively. The descriptive correlational statistics, mean, t-test, ANONA, Pearson correlation coefficient were used to analyze the data gathered with SAS pc+ program. The results were as it follows: 1. The average fatigue score of the subjects was $64.93{\pm}12.89$. Fatigue scores by subcategory were physical symptoms($23.5{\pm}4.87$). psychological symptoms($22.11{\pm}4.66$) and neuro-sensory symptoms($19.32{\pm}5.14$). With the respect to the demographic characteristics of the subjects, there were statistically significant differences between the demographic factors and fatigue, especially, sex(t==3.69 p<0.01), major(t=-2.89 p<0.01). the experience of family illness(t=2.76 p<0.01). 2. The average health promoting life style item score of the subjects was $2.33{\pm}0.33$. In the subcategories, the highest degree of performance was self-actualization(2.94), following interpersonal support(2.81). stress management(2.33), exercise(2.20), nutrition(2.10), and the lowest degree was health responsibility(1.73). There were the significant differences on the learning of health education(t=2.00 p<0.01). religion(F=3.01, p<0.05), circle activity(t=2.07, p<0.05), nutrition control(t=5.25, p<0.01) of demographical factors with the health promoting life style. 3. The correlation between the fatigue and health promoting life style made statistically no significance(r=-0.09731, p>0.05). But there was negative significant relationship between health promoting life style and psychological symptom as a fatigue subcategory(r=-0.15721, p<0.05). The self-actualization showed negative significant correlation with all fatigue subcategory. The health responsibility showed significant relationship with total fatigue(r=0.13050. p<0.05). For further research, it suggests to replicate the correlational and causal study between the fatigue and the health promoting life style using the another fatigue scale which is able to measure the subjective and objective fatigue degree. And it needs to develop the nursing intervention program for maintaining and promoting the health behavior as well as for decreasing the college students's fatigue.

• Journal of Digital Convergence
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• v.18 no.1
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• pp.301-307
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• 2020

In recent years, a recommendation system is introduced in many different fields with the beginning of the 5G era and making a considerably prominent appearance mainly in books, movies, and music. In such a recommendation system, however, the preference degrees of users are subjective and uncertain, which means that it is difficult to provide accurate recommendation service. There should be huge amounts of learning data and more accurate estimation technologies in order to improve the performance of a recommendation system. Trying to solve this problem, this study proposed a movie recommendation system based on Fuzzy-AHP and Word2vec. The proposed system used Fuzzy-AHP to make objective predictions about user preference and Word2vec to classify scraped data. The performance of the system was assessed by measuring the accuracy of Word2vec outcomes based on grid search and comparing movie ratings predicted by the system with those by the audience. The results show that the optimal accuracy of cross validation was 91.4%, which means excellent performance. The differences in move ratings between the system and the audience were compared with the Fuzzy-AHP system, and it was superior at approximately 10%.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.47-56
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• 2012

The purpose of this study is to test the effect of pedagogical agent realism and expertise on persona effect. There were two perspectives of the pedagogical agents' social interaction. Self-identification hypothesis argues that complexity of agent image is better to increase social interaction. Subjective identification insists that simplified image is more helpful to facilitate social interaction. However, from the cognitive load theory perspective, learners' expertise can be a major factor to determine persona effect. Sixty-eight college students (male=19 and female=49) participated. The independent variables were the degree of realism of pedagogical agent (detailed vs. simplified image) and the expertise (high prior knowledge group vs. low prior knowledge group). The dependant variables were comprehension test and the agent persona instrument (API). There was no significant difference in comprehension test score; however, there were significant interaction effect on the most constructs of API: 1) facilitating of learning, 2) credible, and 3) human-like. The follow-up analysis of simple main effect revealed that high expertise group showed significantly higher perception of the three construct with high realism of pedagogical agent. The results of study show that learners' expertise plays a key role of perception of persona effect.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1372-1380
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• 1999

본 논문에서는 자연언어 문장의 객관적 정량적인 질 측정 방법의 구축에 대해 설명하고, 이를 문장 퇴고 시스템의 사례에 적용해 본다. 문장의 질을 평가한다는 것은 본질적으로 주관적이고 정량화가 어려운 작업이기 때문에, 이 과정에서 질의 객관적 계량화가 가능한지 여부가 가장 중요한 문제가 된다. 이 논문에서는 이러한 문제를 해결하기 위해 유전자 알고리즘을 이용한 진화적 접근 방법을 통해 객관적이고 정량적인 질의 측정 공식을 유도하는 방법론을 제시하였다. 이 논문에서 제시한 방법론의 핵심은 간단히 말해서 사람이 행하는 정성적인 판단을, 이에 가장 근접하는 정량적 측정 체계로 전환시키는 것이라고 보면 된다. 이것을 위해 정량화 문제를 문장의 단순 언어 특징들의 변화값을 이용한 최적화 문제로 환원시키고, 다시 이 최적화 문제를 유전자 알고리즘을 이용해 해결함으로써 문제를 효과적으로 해결할 수 있었다. 실험 결과를 보면, 본 논문에서 제시한 최적화 방법은 주어진 훈련용 예제와 검증용 예제 중 각각 99.84%, 99.88%를 만족시키는 해를 찾아내었으므로 정량적 질 평가 공식의 유도에 매우 효과적임을 알 수 있었다. 또한 도출된 측정 공식을 이용해서 실제 퇴고 시스템 평가에 적용한 결과 문장 질의 측정에 매우 유용하게 이용될 수 있음을 알 수 있었다. 이와 같이 질의 정량적 평가가 가능하다는 사실이 갖는 또 한가지 중요한 의미는 최종 사용자의 구매 의사나 개발자의 공학적 의사 결정을 위한 객관적 성능 평가 자료의 제공에 이 방법이 유용하게 사용될 수 있다는 점이다.Abstract This paper describes a method of building a quantitative measure of the quality of natural language sentences, particularly produced by document revision systems. Evaluating the quality of natural language sentences is intrinsically subjective, so what is most important as to the evaluation is whether the quality can be measured objectively. To solve such problem of objective measurability, genetic algorithm, an evolutionary learning method, is employed in this paper. The underlying standpoint of this approach is that building the quality measures is a task of constructing a formulae that produces as close results as can to the qualitative decisions made by humans. For doing this, the problem of measurability has been simply reduced to an optimization problem using the change of the values of simple linguistic parameters found in sentences, and the reduced problem has been solved effectively by the genetic algorithm. Experimental result shows that the optimization task satisfied 99.84% and 99.88% of the given objectives for training and validation samples, respectively, which means the method is quite effective in constructing the quantitative measure of the quality of natural language sentences. The actual evaluation result of a revision system shows that the measure is useful to quantize the quality of sentences. Another important contribution of this measure would be to provide an objective performance evaluation data of natural language systems on a basis of which end-users and developers can make their decision to fit their own needs.