• Journal of Korean Home Economics Education Association
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• v.33 no.2
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• pp.57-80
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• 2021

The purpose of this research is to develop a Home Economics education curriculum that can promote citizenship through critical literacy. To this end, the 'housing' area in the 2015 revised curriculum of home economics and textbooks were analyzed from a critical literacy perspective. Using Laster(1986)'s critical science curriculum development course and "A Teacher's guideFamily, Food and Society"(Staaland & Storm, 1996), a 'Citizenship raising curriculum of home economics education in the housing area.' was developed. The results of this research are as follows. First, when the the curriculum was examined, the teaching objectives of the overall subject, or the achievement criteria, learning elements, and evluative methods of the housing area consisted of practical problem solving curriculum that can include critical literacy content. In addition, as a result of analyzing the text of the three textbooks' housing areas, it was found that most of them were described as adapting to and coping with the current culture, and few problems or social issues were mentioned that could lead to critical literacy. Second, the housing area curriculum for critical literacy learning was developed, with a total of 13 plan of 7 modules including continuous interests, valued ends, learning contents, and 26 learning materials including reading materials, and video materials. Based on the findings, the next curriculum and textbook should address social issues related to critical literacy and various classes of housing, and teachers' communities and training should be operated to support teachers who can be examplary for practical reasoning and critical thinking.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.113-123
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• 2020

In this paper, big data analysis was conducted for past and present fashion trends and fashion cycle. We focused on daily look for ordinary people instead of the fashion professionals and fashion show. Using the social matrix tool, Textom, we performed frequency analysis, N-gram analysis, network analysis and structural equivalence analysis on the big data containing fashion trends and cycles. The results are as follows. First, this study extracted the major key words related to fashion trends for the daily look from the past(1980s, 1990s) and the present(2019 and 2020). Second, the frequence analysis and N-gram analysis showed that the fashion cycle has shorten to 30-40 years. Third, the structural equivalence analysis found the four representative clusters. The past four clusters are jean, retro codi, athleisure look, celebrity retro and the present clusters are retro, newtro, lady chic, retro futurism. Fourth, through the network analysis and N-gram analysis, it turned out that the past fashion is reproduced and evolves to the current fashion with certain reasoning.

• 동북아역사논총
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• no.60
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• pp.196-227
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• 2018

The issues of this study are as follows. First, I will examine the overall situation and transition trends of Tibetan research in Taiwan since the modern period, and examine the development and trends of Tibetan history research in Taiwan. Secondly, in order to satisfy the above, we will analyze trends of Taiwan's major Tibetan research institutes and scholars, and trace their trends and their trajectories. Third, the trend of Tibetan research in Taiwan may be a useful indicator for us to analyze research methods and trends of Taiwanese scholars. If there is a flow of features and transitions, the text will explore the reason. Fourth, one of the implications of this study is that it can trigger an understanding of locality in the structure of the central region, the Han Chinese minority, and the possession and distribution of academic reasoning. In other words, it should be noted that even though the same Tibetan research is conducted, China is in the position of the vested right to distribute 226 | 동북아역사논총 60호the central or ownership, while Taiwan has historical and territorial characteristics that deviate from such a gaze and attitude. Taiwan may be sensitive to the vertical concept understood as a change in the relationship between the state and the center, or whether it is applicable to Tibetan research. If there is such an academic climate, I would like to consider suggestions for us. This may provide a direction to view the academic issues of a few scholars, or even the domestic academic world as an independent object of more specific academic research.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• The Journal of Korean Philosophical History
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• no.36
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• pp.101-133
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• 2013

In this paper, the writer investigated the thoughts on military art and science with a focus on the typical books on military art and science, which was published in the latter period of Joseon, and the discussion of literati in that time. Joseon had been happy to enjoy the piping times of peace for about 200 years ever since the establishment of the dynasty. However, having had to gone through two major wars, the Joseon Dynasty, revolving around scholarly people, had awakened the limits of military art and science of Joseon. It can be said that the countermeasure against Japanese pirates, which were reflected in the "Jingbirok" (懲毖錄 - Records of the 1592 Japanese Invasion) written by Yu Seong-ryong, and the experiences of war had formed the basis of the thoughts on military art and science in the latter period. Regrettably, there were no suggestions or proposals of preparing countermeasure against Japanese raiders in the books of military art and science in the early period of the Joseon Dynasty. Meanwhile, as the argument about the battle formation in the early period of Joseon, the process of establishing the military science had not gone smoothly in the latter period of Joseon. Right after the Japanese invasion of 1592, "Gihyo-Sinseo" (紀效新書 - New Text of Practical Tactics written by Cheok Gye-gwang) was brought into the country by the army of Ming (明) Dynasty. At first, this was used in the form of its original edition, or of abstract version in the military drill. But, later, it was published under the title of "Byeonghak-jinam" (兵學指南 - Military Training Manual about Action Rules by combat situation). This book, same as in Zhejian (浙江) province in China, had achieved a positive effect on counteracting the Japanese raiders in our country. However, these military tactics were conflicted with "Owi Jinbeop" - Rules of Deployment of the Five Military Commands, which had been handed down ever since the early period of the Joseon Dynasty, and, at the same time, it was pointed out that those tactics would not be able to apply to the situation uniformly, since Korea and China were geographically different. Furthermore, having gone through Manchu Invasion of 1636 (丙子胡亂, Byeongja horan) Joseon had used "Yeonbyeongsilgi" (練兵實記 - the Actual Records of Training Army), which was compiled in China on the basis of the experiences of wars against the nomad, including Mongolia and so on. And, this had become a typical training manual together with "Byeonghak-jinam". King Yeong Jo and King Jeong Jo of the Joseon Dynasty had tried to establish uniformity in military training by publishing the books of military science representing the latter period of Joseon such as "Sokbyeongjangdoseol" (續兵將圖說- Revision of the Illustrated Manual of Military Training and Tactics,) "Byeonghaktong" (兵學通 Book on Military Art and Science,) "Byeonghakjinamyeonui" (兵學指南演義 - Commentary on 'Byeonghak-jinam') and "Muyedobotongji"(武藝圖譜通志 - Comprehensive Illustrated Manual of Martial Arts,) and so on. King Jeong Jo had actively participated in the arguments in those days. So then the arguments that had been continued for about 200 years, ever since King Seon Jo, put to an end. To sum up the distinctive features of military art and science in both former and latter period of the Joseon Dynasty, in the former period of Joseon, the reasoning military science was proceeded with the initiative of civic official based on "Mugyeongchilseo"(武經七書- the Seven Military Classics). However, in the latter period of Joseon, "Gihyo-Sinseo"(紀效新書 - New Text of Practical Tactics written by Cheok Gye-gwang) had served as a momentum, and also comparatively a large numbers of military official had participated in arguments, so then such an occasion had made the military science turn into the Practical Theory. Meanwhile, King Sejo and King Jeong Jo had played a leading role in the process of establishing the theory of military science of Joseon, however, there are something in common that their succession to the throne was not smooth. This is the part that reminds us "War is an extension of politics," the thesis of Clausewitz

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.139-157
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• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.79-96
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• 2008

One of the roles of the Semantic Web services is to execute dynamic intra-organizational services including the integration and interoperation of business processes. Since different organizations design their processes differently, the retrieval of similar semantic business processes is necessary in order to support inter-organizational collaborations. Most approaches for finding services that have certain features and support certain business processes have relied on some type of logical reasoning and exact matching. This paper presents our approach of using imprecise matching for expanding results from an exact matching engine to query the OWL(Web Ontology Language) MIT Process Handbook. MIT Process Handbook is an electronic repository of best-practice business processes. The Handbook is intended to help people: (1) redesigning organizational processes, (2) inventing new processes, and (3) sharing ideas about organizational practices. In order to use the MIT Process Handbook for process retrieval experiments, we had to export it into an OWL-based format. We model the Process Handbook meta-model in OWL and export the processes in the Handbook as instances of the meta-model. Next, we need to find a sizable number of queries and their corresponding correct answers in the Process Handbook. Many previous studies devised artificial dataset composed of randomly generated numbers without real meaning and used subjective ratings for correct answers and similarity values between processes. To generate a semantic-preserving test data set, we create 20 variants for each target process that are syntactically different but semantically equivalent using mutation operators. These variants represent the correct answers of the target process. We devise diverse similarity algorithms based on values of process attributes and structures of business processes. We use simple similarity algorithms for text retrieval such as TF-IDF and Levenshtein edit distance to devise our approaches, and utilize tree edit distance measure because semantic processes are appeared to have a graph structure. Also, we design similarity algorithms considering similarity of process structure such as part process, goal, and exception. Since we can identify relationships between semantic process and its subcomponents, this information can be utilized for calculating similarities between processes. Dice's coefficient and Jaccard similarity measures are utilized to calculate portion of overlaps between processes in diverse ways. We perform retrieval experiments to compare the performance of the devised similarity algorithms. We measure the retrieval performance in terms of precision, recall and F measure? the harmonic mean of precision and recall. The tree edit distance shows the poorest performance in terms of all measures. TF-IDF and the method incorporating TF-IDF measure and Levenshtein edit distance show better performances than other devised methods. These two measures are focused on similarity between name and descriptions of process. In addition, we calculate rank correlation coefficient, Kendall's tau b, between the number of process mutations and ranking of similarity values among the mutation sets. In this experiment, similarity measures based on process structure, such as Dice's, Jaccard, and derivatives of these measures, show greater coefficient than measures based on values of process attributes. However, the Lev-TFIDF-JaccardAll measure considering process structure and attributes' values together shows reasonably better performances in these two experiments. For retrieving semantic process, we can think that it's better to consider diverse aspects of process similarity such as process structure and values of process attributes. We generate semantic process data and its dataset for retrieval experiment from MIT Process Handbook repository. We suggest imprecise query algorithms that expand retrieval results from exact matching engine such as SPARQL, and compare the retrieval performances of the similarity algorithms. For the limitations and future work, we need to perform experiments with other dataset from other domain. And, since there are many similarity values from diverse measures, we may find better ways to identify relevant processes by applying these values simultaneously.

• Journal of Service Research and Studies
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• v.10 no.3
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• pp.23-42
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• 2020

This study conceptualized the essence and propensity of modern management in service age, based on philosophy, and developed items to evaluate the conceptualized content. It was carried out as a new study to deepen the study of management philosophy and management theory by the new management framework. In order to establish the philosophical foundation of the modern management, the essence of the modern management was conceptualized based on the fundamental ideas of the East and West, and then an evaluation item was developed to put the essence and propensity of the modern management into practical use through analytical and empirical methods. After analyzing the representative ideas of mankind, it was derived that the Book of Change has the qualification as a philosophical model that can derive the essence of modern management. The Book of Change explains the reasoning of the world in the structure of two opposing parties, such as Taiji or Yin and Yang, and the process of acknowledging the contradictions within each opposing party and overcoming the contradictions through change is the central idea. Because you can see. After conducting a conceptual study, through empirical research, the essence and propensity of a modern manager should be conceptualized. The concept of essence and empirical study of the modern management using the leading role was conducted in two stages. First, a qualitative study using repetitive comparative analysis (CCM), focus group interview (FGI), and text mining was conducted to derive the essential and propensity conceptualization items that modern managers should possess. In addition, a quantitative study using factor analysis to develop sample items and develop measurement items through literature review and FGI was conducted to derive the essential concept of the modern management. Finally, the essence of modern management was derived: learning, preparation, challenge, inclusion, trust, morality, and sacrifice. In the future, it is necessary to conduct empirical research on the effectiveness of the essence of modern management for global and Korean representative companies.

• Journal of Science of Art and Design
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• v.10
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• pp.5-50
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• 2006

The terminology "human body" simply means a physical body but also more often, as an object in art works, carries symbolic concepts incorporating the whole history of human lives. Human body has been employed as an artistic object capturing physical body, delivering artist's idea expressing life indicators from different standpoints of times and places. This point of view about human body in art works has in fact rather short history since 1960's when modern thinking paradigm focusing upon rationality and reasoning has begun declining and on the contrary when the body used to be the servant of the mind and soul for a long time has begun attracting artist's attention as a real entity from the viewpoint of dichotomy. During the 1960's, frequent performances in Pop art and of Fluxus showed that the human body has been an important media for artistic communication after importance of body performances had been raised in Action painting in 1940's. The human body became a more determined media in body art works that had got into stride after Yves Kline's conceptual works applying body and its traces. These kinds of art works have continued and consolidated into the Feminism came into blossom in 1980's and into fragmentated and disembodied body art trend in 1990's. Through development of trends in body works, human body now might well be regarded as a clue provide from individual identity with implication over the world. This thesis is to analyse in semiotic way main works of Kiki Smith who is a representative artist devoting to Feminism and proposing extended significance of human body. In the analysis process of works done by two great artists with histrorical background of art trend in order to find and open an significance horizon of human body, semiotics and bodism are therefore perceived as pertinent and applied as basic tools. The first stage of analysis is to get the significances emerged in between expression part and contextual parts, which are separated structually from the most basic level. The study deals with body works furthermore in the way of structual cohesion of the expression and the context from the view of A J. Greimas' Structural Semantics and tried to build up a basic frame for the extended significances of human body. This thesis is, on the other hand, to attempt to contribute for extension of disembodied and fragmentated body discussed in the structural semantic frame earlier by Julia Kriesteva who delivers abjection concepts and phenomenology of Maurice Merleau-Ponty who enables to overview relationship between the body and the world from the viewpoint of Bodism, further into interpretation level. The other works are Kiki smith's that showed epics about death in mid-1980's, detailed humbleness of vulnerable human body exposed to dichotomy and fragmentation in 1990's and religion and mythology incorporating wouln healing in 2000's and henceforth. Through the analysis of Kiki Smith's representative work 'Pee body', it is verified and confirmed that fragmentated body showed beyond boundary gap of the human body and ultimately tends to imply human healing owing to divine maternity. Bodily symbols in Kiki Smith's are extended to the universal world to imply human life and death on the one hand and religion and mythology of human wound and divine healing one the other hand. This thesis through these process and results of analysis is in a broad context, to emphasize that human body as objectified text has a key indicator role to understand world as well as semiotic extension in art works in late 20th century so that we might confirm bodily symbol as a cultural context constitutes a section of contemporary visual arts.