• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.116-124
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• 2018

This study aimed to interpreting the view of current media by artificial intelligence(AI) with the case of a TV show Person of Interest, which was broadcasted until 2016 in US. In this study, we first attempted to find how AI reflects the three laws of robotics, which often appear in Science Fictions. In addition, we paid attention to how the society looks according to the change of the manipulator of the AI, and as a result we derived the distinguishes of the show from other content dealing with robots or AI in terms of narrative. Through this study, we classified the messages in accordance of AI into three categories- importance of data sovereignty, potential of intelligence explosion, and blind faith in high technology. This study suggested that the show emphasizes the consciousness and attitude that should be possessed as a citizen who meets the era of AI prior to raising issue of 'what artificial intelligence is should be developed for our convenience?'

• Archives of Plastic Surgery
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• v.35 no.2
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• pp.127-133
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• 2008

Purpose: The purpose of this study is to evaluate the remodeling process of the various skin substitutes in 4th and 6th weeks following the transplantation when transplanted onto nude mice. Methods: Three types of artificial skin substitutes, such as PLGA scaffold with keratinocyte sheets(group 1), acellular human dermis($Surederm^{(TM)}$) and keratinocyte sheet(group 2), bioengineered skin($Neoderm^{(TM)}$)(group 3), were applied to the wound on nude mice. All mice were killed in 2, 4 weeks and/or 6 weeks after grafting and tissue samples were harvested from the back of mice. The changes in wound size, degree of angiogenesis, formation of basement membrane and epidermis, density of collagen fibers and neural restoration were examined. Results: There was no significant changes in wound size among the three groups. However, the size of wound decreased in the non-substituted group due to contracture. Degree of angiogenesis and systhesis of collagen or neurofilaments were mostly increased in bioengineered skin($Neoderm^{(TM)}$)(group 3), followed by acellular human dermis($Surederm^{(TM)}$) and keratinocyte sheet(group 2), PLGA scaffold with keratinocyte sheets (group 1). However, group 3 and group 2 showed similar thickness of basement membrane and epidermis. Conclusion: We found that degree of angiogenesis, formation of basement membrane and skin appendages, density of collagen fibers and neurofilaments can be the categories to evaluate the success of artificial skin substitution in early stages.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Korean Institute of Interior Design Journal
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• v.19 no.4
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• pp.22-30
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• 2010

Light has primary function to enlighten the darkness. However, as development and progresses in media has caused big change in our life, the range of usage and application of light is broadened. And these days, light is actively used as a communication tool in a space. This thesis is based on an idea that a new prospect of light is required and at the same time the theoretical foundation should be established to take active advantage of light. In Chapter two, analysis criteria are established to verify study hypothesis. The applied methodology is to analysis the contents based on literature review. Key words related light in space design are extracted and the frequency of those key words are quantitatively measured. Taking advantage of the result, the characteristics of light are divided into three categories, 'light as symbolic information', 'light as communication medium' and 'light as topological form'. In chapter three, analysis of cases is performed. The cases are selected based on space analyzing criteria established in Chapter two. Qualitative analysis is performed on the cases categorized into natural light and artificial light. Basic analysis elements are evaluated for each case. And each case is allocated to one of three categories, 'light as symbolic information', 'light as communication medium' and 'light as topological form'. Through this analysis, it is found that light in space has prevailing characteristics of 'light as symbolic information' and 'light as communication medium'.

• Hwankyungkyoyuk
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• v.19 no.3
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• pp.138-149
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• 2006

The purpose of this study was to develop the environmental sensitivity(ES) measurement instrument and to apply for middle school students. The questionnaire was developed to evaluate ES. The developed questionnaire consists of 15 items in 5 categories. Each item of the instrument was developed through the conceptional analysis of the definition of ES. The 5 categories included natural environment, activity at natural environment, artificial environment, environmental pollution, environmental destruction. Data for this study were collected from 397 middle school students including 46 environmental class and 351 non-environmental class students. It was found that the developed instrument to measure ES was valid and reliable. Reliability coefficient, Cronbach $\alpha$ was 0.75. Using the developed instrument of ES, the ES was measured for the students of experimental group to which a inqury-based EE model was applied. The result was that the effect of ES of the students of the experimental group was not statistically significant. Futher research is needed related to the EE model based on the inquiry learning model and measurement of environmental sensitivity.

• The Research Journal of the Costume Culture
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• v.19 no.5
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• pp.957-969
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• 2011

This study intended to analyze the grunge look as a mode of expression and as a characteristic of the fashion of the 21st century, arguing that the look expressed not only an outward appearance or sub-culture but also a change in our attitude and spirit about contemporary fashion. In the study, I carried out an empirical analysis focused on the collection from 2001S/S to 2010F/W and a literature review. In my results, I classified the grunge look into the following categories: 1. mix and match layering; 2. patchwork, collages, and assemblage using all objects as well as clothing materials; and 3. distressing techniques, such as bleaching and dyeing, unweaving, and tears and holes. I also classified the characteristics of grunge into the following categories: 1. conspicuous destitution, which is intentionally expressed by skillful techniques and craftsmanship, indicating that modern people want to attract attention and be distinguished from others, which reflects an attitude of superiority through ironic fashion choices; 2. high lighting the dissolution of decoration, where destruction, poverty and recombination shown in the grunge look emerged as an artificial and intentional ugly aesthetic in contrast to the existing elegant and sophisticated image; and 3. satire and playfulness, as grunge expresses alienation and conflict in modern society through satire and sarcasm, not attacking or avoiding, but through playful and sarcastic engagement so as to decrease poverty and give temporary freedom.

• Journal of the Korean housing association
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• v.18 no.1
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• pp.83-93
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• 2007

Following the previous ones, this study is intended to explore methods of qualitative assessment on the view from apartment units. It first complemented and analyzed the attributes of landscape elements and then set up questionnaire items based on these attributes to identify the tendencies in apartment inhabitants' recognition of landscape elements, and then conducted a preference assessment on the test cases sampled on the basis of picture and other data collected in the previous studies to identify the characteristics of the preference for the view from apartment units according to landscape elements. Consequently, the following results have been derived. First, the landscape elements seen from apartment units may be classified into a total of sixteen categories, and the overall ratio of natural elements to artificial ones is shown to be approximately one to three. Second, it is also shown that apartment dwellers tend to prefer natural landscape elements over artificial ones, and the preferences for the distance to and location of landscape elements exhibit certain variance depending on the type of the elements. Third, the analysis of the preference for landscape elements has revealed that the types of landscape elements, the make-up and diversity of landscape elements, and the perceived distance to landscape elements as well as the resultant feeling of openness all affect the preference tendencies.

• Computers and Concrete
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• v.13 no.6
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• pp.765-780
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• 2014

Many building codes use the empirical equation to determine fundamental period of vibration where in effect of length, width and the stiffness of the building is not explicitly accounted for. In the present study, ANN models are developed in three categories, varying the number of input parameters in each category. Input parameters are chosen to represent mass, stiffness and geometry of the buildings indirectly. Total numbers of 206 buildings are analyzed out of which, data set of 142 buildings is used to develop these models. It is demonstrated through developed ANN models that geometry of the building and the sizes of the columns are significant parameters in the dynamic analysis of building frames. The testing dataset of these three models is used to obtain the empirical relationship between the height of the building and fundamental period of vibration and compared with the similar equations proposed by other researchers. Experiments are conducted on Mild Steel frames using uniaxial shake table. It is seen that the values obtained through the ANN models are close to the experimental values. The validity of ANN technique is verified by experimental values.

• Journal of Korea Multimedia Society
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• v.24 no.7
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• pp.880-889
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• 2021

In everyday life, recognizing people's emotions from their frames is essential and is a popular research domain in the area of computer vision. Visual emotion has a severe class imbalance in which most of the data are distributed in specific categories. The existing methods do not consider class imbalance and used accuracy as the performance metric, which is not suitable for evaluating the performance of the imbalanced dataset. Therefore, we proposed a method for recognizing visual emotion using balanced data augmentation to address the class imbalance. The proposed method generates a balanced dataset by adopting the random over-sampling and image transformation methods. Also, the proposed method uses the Focal loss as a loss function, which can mitigate the class imbalance by down weighting the well-classified samples. EfficientNet, which is the state-of-the-art method for image classification is used to recognize visual emotion. We compare the performance of the proposed method with that of conventional methods by using a public dataset. The experimental results show that the proposed method increases the F1 score by 40% compared with the method without data augmentation, mitigating class imbalance without loss of classification accuracy.

• STI Policy Review
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• v.9 no.1
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• pp.133-157
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• 2018

The divide between the "digital" economy and the traditional "physical" economy is outdated. In fact, we are in a transition to a singular economy. This paper classifies economic objects (including actors) as either physical or virtual and argues that due to emerging technologies, these objects are interacting with each other in both physical and increasingly digital spheres in tandem. This paper recognizes the elemental difference between atoms and bytes but argues that physical and digital economic activities are becoming inseparably intertwined. Furthermore, arbitrarily dividing the economy into two categories - one "physical" and the other "digital" - distorts the overall view of the actual execution of economic activity. A wide range of innovations emerging concurrently is fueling the transition to a singular economy. Often referred to as the elements of the Fourth Industrial Revolution (4IR), four emerging technological areas are reviewed here: distributed ledger technology, artificial intelligence/machine learning/data sciences, biometrics and remote sensor technologies, and access infrastructure (universal internet access/electricity/cloud computing). The financial services sector is presented as a case study for the potential impact of these 4IR technologies and the blurring physical/digital line. To reach the potential of these innovations and a truly singular economy, it requires the concurrent development of social, organizational, and regulatory innovations, though they lag in terms of technological progress thus far.