• The Journal of Korean Association of Computer Education
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• v.22 no.1
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• pp.63-78
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• 2019

This study aims to improve User eXperience (UX) of the diagnostic-supplement learning system for Basic academic skills which has been utilized by teachers nationwide since 2015 in order to provide a consistent and systematic support on students' basic academic skills in K-12 school contexts. To achieve the research objective, usability evaluations such as basic questionnaire about UX/UI of the system according to user types, user testing, in-depth interview, expert heuristics were conducted. In addition, user-centered system was suggested through developing and iteratively evaluating the prototypes based on the user requirements drawn from the findings of such quantitative and qualitative usability evaluations. This study has an implication in suggesting the user-friendly design through the UX/UI improvements of the diagnostic-supplement learning system for Basic academic skills.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.99-111
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• 2019

With the low birth rate and the inner city decline, the number of small schools is expected to increase. In this trend, the Ministry of Education has consistently used the number of students as a standard for the merger and abolition of schools since 1982, but it seems that has generated a vicious circle of education in rural areas and also it did not reflect realistic requirements and changes in the times although it is efficiency of local education finances. With the number of students constantly decreasing, it has a high probability to make villages without schools in urban areas if decisions are made by the number of students. In this sense, it is suggested that regional contexts and socioeconomic environment should be taken into account rather than to conduct the merger and abolition of small schools with economic logic. It is necessary to change the direction of improving the quality of education through the operation of small schools for coexistence of schools and villages and a cultivating the manpower needed in the 21st century knowledge information society and the 4th industrial revolution era. Therefore, we tried to find tasks for expanding small schools of the local community and developing small schools suitable for future social change.

• Database Research
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• v.34 no.3
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• pp.99-123
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• 2018

Due to the ever expanding nature of the Web, separating more valuable information from the noisy data is getting more important. Although recommendation systems are widely used for addressing the information overloading issue, their performance does not seem meaningfully improved in currently suggested approaches. Hence, to investigate the issues, this study discusses different characteristics of popular, existing recommendation approaches, and proposes a new profiling technique that uses collaborative tags and test whether it successfully compensates the limitations of the existing approaches. In addition, the study also empirically evaluates rating/tagging patterns of users in various recommendation approaches, which include the proposed approach, to learn whether those patterns can be used as effective cues for improving the recommendations accuracy. Through the sensitivity analyses, this study also suggests the potential associated with a single recommendation system that applies multiple approaches for different users or items depending upon the types and contexts of recommendations.

• Korean Journal of Family Welfare
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• v.23 no.4
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• pp.633-652
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• 2018

This study aimed to examine the direct effects of relationships with parents, peers, and community child center teachers on the school adjustment of low-income adolescents attending community child centers and the indirect effects mediated through adolescents' resilience. The second-term panel data from the fourth-year Community Child Center Survey was used to analyze 198 adolescents (103 boys, 95 girls) who were first graders at middle schools. SPSS 20.0 and AMOS 20.0 were used to analyze the data through structural equation modeling. The results of the study were as follows: Parental monitoring and peer trust had direct effects on the adolescents' school adjustment, while satisfaction with community child center teachers did not. Parental monitoring, peer trust, and satisfaction with community child center teachers had indirect effects on adolescents' school adjustment mediated through resilience. The school adjustment of low-income adolescents has received attention from both researchers and politicians. The results of this study are notable in that both the important relationships and resilience of low-income adolescents can significantly contribute to their school adjustment in their first year at middle school. Given the developmental needs of low-income adolescents, interventions for school adjustment that consider adolescents' important social contexts and psychological characteristics should be developed.

• Journal of IKEEE
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• v.22 no.4
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• pp.1123-1130
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• 2018

A cat robot for the Autism Spectrum Disorders(ASD) treatment was designed and conducted field test. The designed robot had emotion expressing action through interaction by the touch, and performed a reasonable emotional expression based on Artificial Neural Network(ANN). However these operations were difficult to use in the various healing activities. In this paper, we describe a motion design that can be used in a variety of contexts and flexibly reaction with various kinds of situations. As a necessary element, the speech recognition system using the speech data collection method and ANN was suggested and the classification results were analyzed after experiment. This ANN will be improved through collecting various voice data to raise the accuracy in the future and checked the effectiveness through field test.

• International Area Studies Review
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• v.13 no.2
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• pp.789-812
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• 2009

This paper aims to analyse the historical-cultural sources of Azerbaijani national identity through the aspects of the Persian, the Turkish and the Russian influences, and to illuminate its complex characteristics. Then it will be examined the impact and consequences that the Azerbaijani identity exerted on its foreign policy. In the modern world, identities are formed and represented within a variety of shifting social, political, economic, cultural, and discursive contexts. Such understandings can have exclusionary consequences, particularly in pluralistic environments. Since its independence, the PFA government resorted to the arguments of ethnic origin and Azerbaijan's Turkishness to achieve its goals. Domestically, the failure of the ethnicity-based foreign policy was so great that even Azerbaijani Kurds, who under the Soviets had been virtually absorbed into the Azeri population, felt alienated and betrayed. Internationally, Azerbaijan turned Russia and Iran against itself and reduced bargaining power of Turkey since the latter grew increasingly concerned not to exacerbate its relations with Russia.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.901-904
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• 2014

As sensing techniques have advanced, context-aware technologies have been developed under the various domain for each different purpose. The number of services were created and are being used actually, but the services for specific spatial domain are not adequate yet. To solve this, there have been many efforts, and some of them were actually successful. Among them, the methods which used ontology-based inference were relatively reliable and appropriate for context-aware system, but not able to support contexts for individual without complex rules. In this paper, current scope of context inference is extended from user-oriented context modeling to entity-oriented. Furthermore, we used user profile and home profile to provide more specific context information of not only each individual but entity.

• Korean Journal of Heritage: History & Science
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• v.50 no.2
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• pp.80-93
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• 2017

This study proposes a new scientific measurement method for damaged epigraph. In this new method, the Chinese characters are converted and coordinates are created for this measurement. This method is then used to decipher partially damaged characters from the parts of the coordinated characters that are damaged and intact. The Chinese characters are divided into 9 square parts by the position of their Chinese Radicals. The unknown characters are then compared and deciphered dependent upon the character shape in 9 square parts that have been created. This method is more scientific, accurate, and makes it easier to find related characters than deciphering through contexts, which is current method. When creating a new software based on this algorithm, it will be especially useful in deciphering an old manuscript or a epigraph that made ancient Chinese characters which are not currently in use. This study will also be helpful in deciphering semi-cursive styled or cursive styled epigraph, as well as semi-cursive styled or cursive styled damaged characters during follow-up research.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.375-381
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• 2019

Recently, the recommendation system has attracted the attention of users as customized recommendation services have been provided focusing on fashion, video and music. But these services are difficult to provide users with proper service according to many different contexts because they do not use contextual information emerging in real time. When applied contextual information expands dimensions, it also increases data sparsity and makes it impossible to recommend proper music for users. Trying to solve these problems, our study proposed a music recommendation system to recommend proper music in real time by applying association rules and using relationships and rules about the current location and time information of users. The accuracy of the recommendation system was measured according to location and time information through 5-fold cross validation. As a result, it was found that the accuracy of the recommendation system was improved as contextual information accumulated.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.11-16
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• 2019

People are subject to time sanctions in a busy modern society. Therefore, people find it difficult to eat simple junk food and even exercise, which is bad for their health. As a result, the incidence of chronic diseases is increasing. Also, the importance of making accurate and appropriate inferences to individual characteristics is growing due to unnecessary information overload phenomenon. In this paper, we propose a knowledge reasoning model using association rules and cluster analysis of multi-contexts. The proposed method provides a personalized healthcare to users by generating association rules based on the clusters based on multi-context information. This can reduce the incidence of each disease by inferring the risk for each disease. In addition, the model proposed by the performance assessment shows that the F-measure value is 0.027 higher than the comparison model, and is highly regarded than the comparison model.