• (The) Research of the performance art and culture
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• no.43
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• pp.173-202
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• 2021

During the Korean War, China dispatched 'the Anti-US and Pro-Joseon Comfort' group to North Korea 3 times. The purpose of the comfort group was to comfort the Chinese People's Supporting Soldiers and Joseon People's Army fighting the US imperial forces and at the same time, inform them of China's situation to booster their morale. Another purpose was to promote the socialism construction projects in the new China. Namely, China wanted to propagate various heroic achievements of the Chinese soldiers and accuse the US imperialist soldiers and thereby, inspire Chinese people's international sense and patriotism for the new China to mobilize the people for the war and promote the construction of the new China effectively. The comfort group consisted of diverse classes (laborers, farmers, intellectuals, women, students, soldiers, etc.) in various areas such as politics, military, ethnic, society, culture, education, etc. Their activities were conducted in various forms such as consolation, legwork, meeting and performances. Their activities were full of anger and compassion, sacrifice and emotion, battle and romance, impression and comfort. Such emotion was delivered intact to the Chinese people through the comfort group's propaganda activities back home in China. The Anti-US and Pro-Joseon Comfort' group revealed their identity of socialists New China in terms of their organization and their specific performances. Their identity claimed for democracy and equality, internationalism empathizing world peace and solidarity of the proletariats, and patriotism supporting the communists regime. The comfort group played a role in propagating such identity of new China effectively by crossing the border. It was a political and cultural performance that stipulated the political meaning of the Anti-US and Pro-Joseon Chosun Comfort' group

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.467-475
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• 2014

With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. A pathway is the biological deep knowledge that represents the relations of dynamics and interaction among proteins, genes and cells by a network. A pathway is wildly being used as an important part of a bio-medical big-data analysis. However, a pathway analysis requires a lot of time and effort because a pathway is very diverse and high volume. Also, multidimensional analysis systems for various pathways are nonexistent even now. In this paper, we proposed a pathway analysis system that collects user interest pathways from KEGG pathway database that supports the most widely used pathways, constructs a network based on a hierarchy structure of pathways and analyzes the relations of dynamics and interaction among pathways by clustering and selecting core pathways from the network. Finally, to verify the superiority of our pathway analysis system, we evaluate the performance of our system in various experiments.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.6
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• pp.614-629
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• 2001

As the information-intensive society in 21c based on the environment of global internet is promoted, the software is getting more large and complex, and the demand for the software is increasing briskly. So, it becomes an important issue in academic and industrial field to activate reuse by developing and exchanging the standardized component. Currently, the information services as a product type of each company are provided in foreign market place for reusing a commercial component, but the components which are serviced in each market place are different, insufficient and unstandardized. That is, construction for Component Data Registry based on ISO 11179, is not accomplished. Hence, the national government has stepped up the plan for sending out public component at 2001. Therefore, the systems as a tool for sharing and exchange of data, have to support the meta-information of standardized component. In this paper, we will propose the C_MDR system: a tool to register and manage the standardized meta-information, based upon ISO 11179, for the commercialized common component. The purpose of this system is to systemically share and exchange the data in chain of acceleration of reusing the component. So, we will show the platform of specification for the component meta-information, then define the meta-information according to this platform, also represent the meta-information using XML for enhancing the interoperability of information with other system. Moreover, we will show that three-layered expression make modeling to be simple and understandable. The implementation of this system is to construct a prototype system of the component meta-information through the internet on www, this system uses ASP as a development language and RDBMS Oracle for PC. Thus, we may expect the standardization of the exchanged component metadata, and be able to apply to the exchanged reuse tool.

• Archives of design research
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• v.18 no.1 s.59
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• pp.91-104
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• 2005

In the past, the design education focused on the technique and skill to satisfy the production and consumption activities of a corporation based on beauty and practicality in the industrial age. Now, it's time to switchover to a life-quality enhancing education by harmonizing and meeting the public's physical and mental needs because design education is a character education which enhances the quality of life by uplifting people's aesthetic sense. This paper has emphasized on the importance of public education of design through the theoretical investigation on social environmental changes caused by the emergence of information society,,education problems, public education, and the necessity of design education. The reason why this study should be done has been suggested by investigating the necessity of this research and bringing up the issue. Furthermore, the current status and problems of public education on design have been analyzed. Then, based on the result, the development direction of design education has been suggested. This study can be concluded as follows: First, the design education should change from its vertical structure to a horizontal one. It should be widely spread to the public, getting off from its privatization for a certain group. Second, designers and the public should correct their way of thinking about design. The ordinary people as well as the designers should cultivate their capability to find and take care of design related issues in their everyday lives. Third, all people should be the subject of design education for the public. As a part of cultural education on the public's aesthetic sense, design education should be reborn as a field of study in which a sound public culture can be developed by the integration of human life and culture, exceeding the limit of school curriculum.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.205-225
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• 2018

Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.

• Communications of Mathematical Education
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• v.24 no.1
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• pp.235-257
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• 2010

Contemporary belief is that the creative talented can create new knowledge and lead national development, so lots of countries in the world have interest in Gifted Education. As we well know, U.S.A., England, Russia, Germany, Australia, Israel, and Singapore enforce related laws in Gifted Education to offer Gifted Classes, and our government has also created an Improvement Act in January, 2000 and Enforcement Ordinance for Gifted Improvement Act was also announced in April, 2002. Through this initiation Gifted Education can be possible. Enforcement Ordinance was revised in October, 2008. The main purpose of this revision was to expand the opportunity of Gifted Education to students with special education needs. One of these programs is, the opportunity of Gifted Education to be offered to lots of the Gifted by establishing Special Classes at each school. Also, it is important that the quality of Gifted Education should be combined with the expansion of opportunity for the Gifted. Social opinion is that it will be reckless only to expand the opportunity for the Gifted Education, therefore, assessment on the Teaching and Learning Program for the Gifted is indispensible. In this study, 3 middle schools were selected for the Teaching and Learning Programs in mathematics. Each 1st Grade was reviewed and analyzed through comparative tables between Regular and Gifted Education Programs. Also reviewed was the content of what should be taught, and programs were evaluated on assessment standards which were revised and modified from the present teaching and learning programs in mathematics. Below, research issues were set up to assess the formation of content areas and appropriateness for Teaching and Learning Programs for the Gifted in mathematics. A. Is the formation of special class content areas complying with the 7th national curriculum? 1. Which content areas of regular curriculum is applied in this program? 2. Among Enrichment and Selection in Curriculum for the Gifted, which one is applied in this programs? 3. Are the content areas organized and performed properly? B. Are the Programs for the Gifted appropriate? 1. Are the Educational goals of the Programs aligned with that of Gifted Education in mathematics? 2. Does the content of each program reflect characteristics of mathematical Gifted students and express their mathematical talents? 3. Are Teaching and Learning models and methods diverse enough to express their talents? 4. Can the assessment on each program reflect the Learning goals and content, and enhance Gifted students' thinking ability? The conclusions are as follows: First, the best contents to be taught to the mathematical Gifted were found to be the Numeration, Arithmetic, Geometry, Measurement, Probability, Statistics, Letter and Expression. Also, Enrichment area and Selection area within the curriculum for the Gifted were offered in many ways so that their Giftedness could be fully enhanced. Second, the educational goals of Teaching and Learning Programs for the mathematical Gifted students were in accordance with the directions of mathematical education and philosophy. Also, it reflected that their research ability was successful in reaching the educational goals of improving creativity, thinking ability, problem-solving ability, all of which are required in the set curriculum. In order to accomplish the goals, visualization, symbolization, phasing and exploring strategies were used effectively. Many different of lecturing types, cooperative learning, discovery learning were applied to accomplish the Teaching and Learning model goals. For Teaching and Learning activities, various strategies and models were used to express the students' talents. These activities included experiments, exploration, application, estimation, guess, discussion (conjecture and refutation) reconsideration and so on. There were no mention to the students about evaluation and paper exams. While the program activities were being performed, educational goals and assessment methods were reflected, that is, products, performance assessment, and portfolio were mainly used rather than just paper assessment.