• Communications of Mathematical Education
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• v.24 no.1
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• pp.49-65
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• 2010

The purpose of this study is to encourage the role of domain to consider the teaching of the concept of functions in modeling real situations. To do this, it is analyzed that how to introduce the concept of functions and linear functions in textbooks treated in the 1st grade and the 2nd grade of middle school. This study also reviewed the role of domain in representational activities for modeling real situations using linear functions. In these reviews, it found that many textbooks do not consider the domain in the equations of functions and these graphs and several text books used linear functions for modeling real situations which are not represented by linear functions contextually. It is concluded that the domain of function is an important concept that will be considered any representational activities for functions.

• Review of Culture and Economy
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• v.21 no.2
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• pp.89-109
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• 2018

This paper aims to offer a conceptual framework in the context of culture-driven city branding through strategic design from a cross-disciplinary approach. The key findings identified the followings: Firstly, the phenomenon of culture-driven city brand creation and the use of design value of primary attractions. Secondly, the impact of the design contents of new media in supporting city brand creation. Lastly, the importance of image/text relationships through applying coding theory to enhance city brand communications.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.683-690
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• 2021

The purpose of this study is to identify research trends on artificial intelligence education. We analyzed 164 domestic journal papers related to AI education published since 2016. The criteria for papers analysis are number of publications by year, journal name, research topic, research type, data collection method, research subject, and subject. The main research areas and areas that require further research are reviewed. The method of the study was analyzed based on the topic and summary of the selected papers, but the text was checked if it was unclear. As a result of the study, research on 'artificial intelligence education' started in earnest after 2017, and has been rapidly increasing in recent years. As a result of the analysis, there were many studies on artificial intelligence education programs and content development, and artificial intelligence perception and image. As for the type of research, there were many quantitative studies, and the development research method was used a lot as a data collection method. In the study subjects, elementary school had a high proportion, and in subject, it was found that there were many practicial subject(technology) dealing with artificial intelligence contents.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.35-45
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• 2018

Users are sharing many of contents such as text, image, video, and so on in SNS. There are various information as like as personal interesting, opinion, and relationship in social media contents. Therefore, many of recommendation systems or search systems are being developed through analysis of social media contents. In order to extract subject-related topics of social context being collected from social media channels in developing those system, it is necessary to develop ontologies for semantic analysis. However, it is difficult to develop formal ontology because social media contents have the characteristics of non-formal data. Therefore, we develop a social topic system based on semantic and subject correlation. First of all, an extracting system of social topic based on semantic relationship analyzes semantic correlation and then extracts topics expressing semantic information of corresponding social context. Because the possibility of developing formal ontology expressing fully semantic information of various areas is limited, we develop a self-extensible architecture of ontology for semantic correlation. And then, a classifier of social contents and feed back classifies equivalent subject's social contents and feedbacks for extracting social topics according semantic correlation. The result of analyzing social contents and feedbacks extracts subject keyword, and index by measuring the degree of association based on social topic's semantic correlation. Deep Learning is applied into the process of indexing for improving accuracy and performance of mapping analysis of subject's extracting and semantic correlation. We expect that proposed system provides customized contents for users as well as optimized searching results because of analyzing semantic and subject correlation.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.41-68
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• 2019

Multi-view learning considers data from various viewpoints as well as attempts to integrate various information from data. Multi-view learning has been studied recently and has showed superior performance to a model learned from only a single view. With the introduction of deep learning techniques to a multi-view learning approach, it has showed good results in various fields such as image, text, voice, and video. In this study, we introduce how multi-view learning methods solve various problems faced in human behavior recognition, medical areas, information retrieval and facial expression recognition. In addition, we review data integration principles of multi-view learning methods by classifying traditional multi-view learning methods into data integration, classifiers integration, and representation integration. Finally, we examine how CNN, RNN, RBM, Autoencoder, and GAN, which are commonly used among various deep learning methods, are applied to multi-view learning algorithms. We categorize CNN and RNN-based learning methods as supervised learning, and RBM, Autoencoder, and GAN-based learning methods as unsupervised learning.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.165-166
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• 2019

Big data analysis is the ability to collect, store, manage and analyze data from existing database management tools. Big data refers to large scale data that is generated in a digital environment, is large in size, has a short generation cycle, and includes not only numeric data but also text and image data. Big data is data that is difficult to manage and analyze in the conventional way. It has huge size, various types, fast generation and velocity. Therefore, companies in most industries are making efforts to create value through the application of Big data. In this study, we analyzed the meaning of keyword using Social Matrix, a big data analysis tool of Daum communications. Also, the theoretical implications are presented based on the analysis results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1463-1469
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• 2020

Multimedia information, including video and voice, is highly utilized in that it is easily understood by people. For this reason, applications have been studied which store multimedia information in IoT devices and transmit information in conjunction with smartphones. The problem is that the size of information can be larger than the capacity of IoT devices due to video and image. In this paper, the multimedia content design technique, which takes into account the limitations of storage capacity, was studied when there is a limit of storage capacity. Considering that the video has a higher understanding of information than text, while the capacity is larger, the solution between information comprehension and capacity is sought. The size of static and dynamic media is a variable and the harm is solved in accordance with the linear planning method. Case studies have shown that the design techniques of this paper are useful.

• English & American cultural studies
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• v.17 no.2
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• pp.29-61
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• 2017

Said's Orientalism criticized the European representations on the Middle-East by theorizing orientalism as a discourse. In this text, he explored and criticized the colonial forms of knowledge and language that distorted the image of the colonized. The justification of the discourse of orientalism is derived from the binary system that is originated from Plato which Derrida rejects on the ground that it always privileges one term over the other, that is, colonizer over colonized. Derrida names for this traditional heritage of Western binary system logocentrism which regards logos(the Greek term for speech or reason) as the central principle of language and philosophy, whereas mythos derives its meaning from the logos on the basis of binary oppositions. Thus according to logocentrism, the colonized is merely the defined who can have its meaning from the definers, colonizers. In this paper, utilizing Derrida's a (non)concept called supplement which means both to add on as a surplus and to make up something missing as a mere extra, I propose another alternative interpretation towards the critique of colonial representation by raising internal contradictions in the Platonic dichotomy between logos and mythos embedded in western colonialism discourse, orientalism. I attempt to show that logos(colonizer) and mythos(colonized) is inseparable in itself due to the fact that they exist as supplementary. For this purpose, I demonstrate how colonial binary system constituted and was constituted in terms of language. Through this paper I reinterpret the colonial rationality of privileging 'logos' over 'mythos' by substituting the colonial binary system with the supplement.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1329-1338
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• 2021

There are rarely effective methods to help visually impaired people when they want to know the expiration date of products excepted to only Braille. In this study, we developed an expiration date notification system based on YOLO and OCR for visually impaired people. The handicapped people can automatically know the expiration date of a specific product by using our system without the help of a caregiver, fast and accurately. The proposed system is worked by four different steps: (1) identification of a target product by scanning its barcode; (2) segmentation of an image area with the expiration date using YOLO; (3) classification of the expiration date by OCR: (4) notification of the expiration date by TTS. Our system showed an average classification accuracy of about 86.00% when blindfolded subjects used the proposed system in real-time. This result validates that the proposed system can be potentially used for visually impaired people.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.5
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• pp.29-41
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• 2022

Alien species cause problems in various ecosystems, reduce biodiversity, and destroy ecosystems. Due to these problems, the problem of a management plan is increasing, and it is difficult to accurately identify each individual and calculate the number of individuals, especially when researching alien turtle species such as GPS and PIT based on capture. this study intends to conduct an individual recognition study using a UAV. Recently, UAVs can take various sensor-based photos and easily obtain high-definition image data at low altitudes. Therefore, based on previous studies, this study investigated five variables to be considered in UAV flights and produced a test paper using them. OCR was used to monitor the displayed turtles using the manufactured test paper, and this confirmed the recognition rate. As a result, the use of yellow numbers showed the highest recognition rate. In addition, the minimum threat distance was confirmed to be 3 to 6m, and turtles with a shell size of 6 to 8cm were also identified during the flight. Therefore, we tried to propose an object recognition methodology for turtle display text using OCR, and it is expected to be used as a new turtle monitoring technique.