• Human Ecology Research
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• v.55 no.1
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• pp.67-80
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• 2017

This study develops an the ideal portrait of a human being pursuing in home economics education from a critical science perspective. The practical problem is 'what should the ideal portrait of a human being pursuing in home economics education with a critical science perspective be?' was addressed through a practical reasoning research method with the stages of valued ends, context, alternatives, consequence, and a final plan. The sequential flow of understanding values and contexts established the setting of three valued ends by organizing issues and categorized areas of individuals, families, society, and cultural from a critical science perspective. The ideal portrait of human being was specifically stated, in the self-formation, independent, inter-subjectivity, social participation, and enculturation according to subcategories; in addition, the stated ideal portrait of human being was modified through expert consultations. Alternatives and consequences were reexamined for the validity of the statement and restated as a comprehensive statement of ideal portrait of a human being that included a restatement of the five areas. An ideal portrait of a human being pursuing in home economics education from a critical science perspective was made from alternative ideal portraits of the proposed human being and stated as 'a person who can continually act autonomously in one's life-world.'

• Computers and Concrete
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• v.12 no.2
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• pp.187-209
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• 2013

This paper presents a study on the prediction of transfer length of 13 mm seven-wire prestressing steel strand in pretensioned prestressed concrete members with rectangular cross-section including several material properties and design and manufacture parameters. To this end, a carefully selected database consisting of 207 different cases coming from 18 different sources spanning a variety of practical transfer length prediction situations was compiled. 16 single input features and 5 combined input features are analyzed. A widely used feedforward neural regression model was considered as a representative of several machine learning methods that have already been used in the engineering field. Classical multiple linear regression was also considered in order to comparatively assess performance and robustness in this context. The results show that the implemented model has good prediction and generalization capacity when it is used on large input data sets of practical interest from the engineering point of view. In particular, a neural model is proposed -using only 4 hidden units and 10 input variables-which significantly reduces in 30% and 60% the errors in transfer length prediction when using standard linear regression or fixed formulas, respectively.

• Journal of the Korean housing association
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• v.17 no.3
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• pp.51-60
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• 2006

Ten years have passed since the Demolishing Walls Campaign has started in Daegu. Recently, the campaign influenced to the other cities in Korea, such as Seoul, Incheon and Busan with various names regarding cities' circumstances. In these context, the study aims to highlight the identity of the Demolishing Walls Campaign compare Daegu with other cities where similar movement has started. In addition, the study evaluates the campaign in terms of physical, psychological and economical aspects to suggest some practical suggestion for the development of the campaign based on questionnaire survey. The research findings are as follows. The research shows that the identity of the Daegu Campaign is started by bottom-up approach based on citizens' participation compare with others cities' campaigns which are mainly started by the local government so called top-down method. The Daegu campaign influences the local people aware of their potential abilities in positively improving urban environment. The results of survey also highlights the advantages of green spaces which by the campaign in terms of environmental and economical aspects. Newly generating urban greens accept and store heat which Influences urban microclimate conditions and it possibly affects energy savings of the city. Most of survey participants eager to continue this campaign which shows positive results in various aspects by the local people. Therefore, the city government building a coalition of local people, NGOs, and interest group to keep the identity of the campaign in Daegu.

• Journal of Korean Elementary Science Education
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• v.33 no.4
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• pp.683-699
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• 2014

The purpose of this study was to explore the characteristics of teacher learning and changes in teachers' epistemic beliefs within a learning community of elementary science teachers. Three in-service elementary teachers who majored in elementary science education in a doctoral course of a graduate school of education participated in the study, and learning activities in the teachers' beginning learning community provided a context for the study. Data sources included field notes produced by the researcher who engaged jointly in the teacher learning community as a coach, audio-recordings of the teachers' narratives, and artifacts generated by the teachers during the process of teacher learning. Complementary analyses of these multiple sources of data revealed that epistemic beliefs of the three elementary teachers were different and that each teacher made a different plan of science instruction based on his own epistemic belief even after the learning experiences within the teacher community. It was therefore suggested that science teacher education programs should be organized in consideration of the nature of teachers as constructivist learners and their practical resources.

• ETRI Journal
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• v.38 no.2
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• pp.376-386
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• 2016

Currently, web applications are gaining in prevalence. In a web application, an input may not be appropriately validated, making the web application susceptible to cross-site scripting (XSS), which poses serious security problems for Internet users and websites to whom such trusted web pages belong. A taint inference is a type of information flow analysis technique that is useful in detecting XSS on the client side. However, in existing techniques, two current practical issues have yet to be handled properly. One is URL rewriting, which transforms a standard URL into a clearer and more manageable form. Another is HTML sanitization, which filters an input against blacklists or whitelists of HTML tags or attributes. In this paper, we make an analogy between the taint inference problem and the molecule sequence alignment problem in bioinformatics, and transfer two techniques related to the latter over to the former to solve the aforementioned yet-to-be-handled-properly practical issues. In particular, in our method, URL rewriting is addressed using local sequence alignment and HTML sanitization is modeled by introducing a removal gap penalty. Empirical results demonstrate the effectiveness and efficiency of our method.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.155-158
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• 2008

The needs for digital models of real environment such as 3D terrain or cyber city model are increasing. Most of applications related with modeling and simulation require virtual environment constructed from geospatial information of real world in order to guarantee reliability and accuracy of the simulation. The most fundamental data for building virtual environment, terrain elevation and orthogonal imagery is acquired from optical sensor of satellite or airplane. Providing interoperable and reusable digital model is important to promote practical application of high-resolution satellite imagery. This paper presents the new research regarding representation of geospatial information, especially for 3D shape and appearance of virtual terrain, and describe framework for constructing real-time 3D model of large terrain based on high-resolution satellite imagery. It provides infrastructure of 3D simulation with geographical context. Details of standard-based approach for providing infrastructure of real-time 3D simulation using high-resolution satellite imagery are also presented. This work would facilitate interchange and interoperability across diverse systems and be usable by governments, industry scientists and general public.

• Journal of Distribution Science
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• v.18 no.7
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• pp.19-25
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• 2020

Purpose: This study analyzes service quality of Pivate Brand (PB) productsto provide some academic and practical implications. Research design, data, and methodology: The focus is on how service quality of No Brand, which has recently received much attention, affects brand attitude and, to confirm whether consumers' prior knowledge of PB moderates this effect. A total of 167 men and women in their 20s who have experience using No Brand were surveyed. Hypothesis was verified by using hierarchical regression analysis. Results: a) Tangibles, reliability, empathy, and assurance of service quality for No Brand have a positive effect on brand attitude; b) The moderating effect of prior knowledge is only statistically significant in the context of reliability. Conclusion: This study provides academic and practical implications for establishing differentiated PB strategies. It highlights the effects of service quality and consumer prior knowledge on brand attitude. This suggests that the sub-dimension of PB service quality has a discriminatory effect on the brand attitude of No Brand, and that consumer's prior knowledge of the product influences reliability of service quality. Therefore, consumer's prior knowledge is important in order to increase trust.

• Journal of Information Technology Services
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• v.16 no.4
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• pp.149-160
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• 2017

Sentiment analysis is the process of determining whether a piece of document, text or conversation is positive, negative, neural or other emotion. Sentiment analysis has been applied for several real-world applications, such as chatbot. In the last five years, the practical use of the chatbot has been prevailing in many field of industry. In the chatbot applications, to recognize the user emotion, sentiment analysis must be performed in advance in order to understand the intent of speakers. The specific emotion is more than describing positive or negative sentences. In light of this context, we propose deep learning models for conducting multi-class sentiment analysis for identifying speaker's emotion which is categorized to be joy, fear, guilt, sad, shame, disgust, and anger. Thus, we develop convolutional neural network (CNN), long short term memory (LSTM), and multi-layer neural network models, as deep neural networks models, for detecting emotion in a sentence. In addition, word embedding process was also applied in our research. In our experiments, we have found that long short term memory (LSTM) model performs best compared to convolutional neural networks and multi-layer neural networks. Moreover, we also show the practical applicability of the deep learning models to the sentiment analysis for chatbot.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.111-115
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• 1998

The Internet today is teemed with not only text data but also other media such as sound, still and moving images in a variety of formats. Unlike text, however, that can be retrieved easily with the help of numerous search engines, there has been few way to access data of other media unless the exact location or the URL is known. Multimedia data in the WWW are contained in or linked via anchors in the hyper-documents. They can most reliably be retrieved by analyzing the binary data content, which is far from being practical yet by the current state of the art. Instead we present another technique of searching based on textual descriptions which are found at or around the multimedia objects. The textual description used in this research includes file name (URL), anchor text and its context, alternative descriptions found in ALT HTML tage. These are actually the clues assumedly relevant to the contents. Although not without a possibility of missing or misinterpreting images and sounds, the description-based search is highly practical in terms of computation. The prototype search engine will soon be deployed to the public service through the prestige search engine, InfoDetective, in Korea.

• East Asian mathematical journal
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• v.27 no.2
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• pp.223-242
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• 2011

The fact that Herbart's education has realized in the educational context the Kant's theory of transcendental education by applying Kant's transcendentalism to education is of great significance for education. It also provides an implication for mathematics education that Herbart's education of mathematics education can be applied to mathematics education through an attempt to combine a practical ethics education and an aesthetic emotion education with mathematics education. Both Kant and Herbart clearly show that an only practical, aesthetic education would not exist as a solely theoretical mathematics education cannot. Therefore, these multi-dimensional aspects of mathematics education should be always considered as a whole although there could be a difference in importance among those aspects. It implies that, regardless of the environments for mathematics education, mathematics teachers and students must do mathematics education activities that take into consideration the humanity in its entirety. The theory of mathematics education based on Herbart's education reveals that the entireness of human being should not be neglected in any case. In this regard, Herbart's theory of education shows that mathematics education is an all-inclusive theory of mathematics education that embraces both phenomenon and transcendence.