• The Journal of Korean Society for Radiation Therapy
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• v.16 no.2
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• pp.43-61
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• 2004

Purpose : For qualify improvement in radiotherapy, it is important to set up and evaluate equipment (linac) accurately. In addition, technicians are needed to be fully aware of the equipment's detailed quality and its manual. Therefore, the result of ATP is evaluated and introduced, in order that the technicians are skilled by participating in quality assurance (QA) and understanding the quality of the equipment before clinical use. Method and Material : QA for LINAC 21EX (Varian, US) was done with suppliers its procedure was divided into radiation survey, mechanical test, radiation isocenter test, bean performance, dosimetry, and enhanced dynamic wedge and using X-omat film (Kodak), multidata, densitometer, and electrometer. QA of MLC (Millennium, 120 leaf) attached to LINAC and EPID (Portal vision) were done separately. Result : The leakage dose by survey meter was below the tolerance. In mechanical test, collimater, gantry, and couch rotation were less than 1mm, and the angles were ${\pm}0.1^{\circ}$ for digital and ${\pm}0.5^{\circ}$ for mechanical. The alignment test of the light field and crosshair were evaluated less than 1mm. The (a)symmetrical jaw field was less than ${\pm}0.5mm$. The radiation isocenter test using X-mat film was less than 1mm. The consistency of light field and radiation field was less than ${\pm}0.1mm$. PDD for photon energy was less than ${\pm}1\%$ and for electron energy of $90\%,\;80\%,\;50\%,\;and\;30\%$ were evaluated within the tolerance. Flatness for photon and electron energy was evaluated $2.3\%$ (tolerance $3\%$) and $3\%$ (tolerance $4.5\%$), respectively, and symmetry was $0.45\%$ (tolerance $2\%$) and $0.3\%$ (tolerance $2\%$), respectively. Dosimetry test for short term, MU setting, rep rate, and dose rate accuracy of photon and electron energy was within the tolerance depending on energy, MU, and gantry angle. Conclusion : Accuracy and safety for clinical use of Clinac 21EX was verified through customer acceptance procedure and the quality of the equipment was found out. These can reduce the difficulties in using the equipment. Furthermore, it is useful for clinically treatment of patients by technicians' active participations.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.33-53
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• 2021

In the crossroads of social change caused by the spread of the Fourth Industrial Revolution and the prolonged COVID-19, the Korean government announced the Digital New Deal policy on July 14, 2020. The Digital New Deal policy's primary goal is to create new businesses by accelerating digital transformation in the public sector and industries around data, networks, and artificial intelligence technologies. However, in a rapidly changing social environment, information asymmetry of the future benefits of technology can cause differences in the public's ability to analyze the direction and effectiveness of policies, resulting in uncertainty about the practical effects of policies. On the other hand, the media leads the formation of discourse through communicators' role to disseminate government policies to the public and provides knowledge about specific issues through the news. In other words, as the media coverage of a particular policy increases, the issue concentration increases, which also affects public decision-making. Therefore, the purpose of this study is to verify the dynamic relationship between the media coverage and the stock market on the Korean government's digital New Deal policy using Granger causality, impulse response functions, and variance decomposition analysis. To this end, the daily stock turnover ratio, daily price-earnings ratio, and EWMA volatility of digital technology-based companies related to the digital new deal policy among KOSDAQ listed companies were set as variables. As a result, keyword search volume, daily stock turnover ratio, EWMA volatility have a bi-directional Granger causal relationship with media coverage. And an increase in media coverage has a high impact on keyword search volume on digital new deal policies. Also, the impulse response analysis on media coverage showed a sharp drop in EWMA volatility. The influence gradually increased over time and played a role in mitigating stock market volatility. Based on this study's findings, the amount of media coverage of digital new deals policy has a significant dynamic relationship with the stock market.

• Trans-
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• v.15
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• pp.25-56
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• 2023

VR is a dynamic image simulation technology with very high information density. Among them, spatial depth, temporality, and realism bring an unprecedented sense of immersion to the experience. However, due to its high information density, the information contained in it is very easy to be manipulated, creating an illusion of objectivity. Users need guidance to help them interpret the high density of dynamic image information. Just like setting up navigation interfaces and interactivity in games, interactivity in virtual reality is a way to interpret virtual content. At present, domestic research on VR content is mainly focused on technology exploration and visual aesthetic experience. However, there is still a lack of research on interactive storytelling design, which is an important part of VR content creation. In order to explore a better interactive storytelling model in virtual reality content, this paper analyzes the interactive storytelling features of the VR animated version of <Wolves in the walls> through the methods of literature review and case study. We find that the following rules can be followed when creating VR content: 1. the VR environment should fully utilize the advantages of free movement for users, and users should not be viewed as mere observers. The user's sense of presence should be fully considered when designing interaction modules. Break down the "fourth wall" to encourage audience interaction in the virtual reality environment, and make the hot media of VR "cool". 2.Provide developer-driven narrative in the early stages of the work so that users are not confused about the ambiguous world situation when they first enter a virtual environment with a high degree of freedom. 1.Unlike some games that guide users through text, you can guide them through a more natural interactive approach that adds natural dialog between the user and story characters (NPC). Also, since gaze guidance is an important part of story progression, you should set up spatial scene user gaze guidance elements within it. For example, you can provide eye-following cues, motion cues, language cues, and more. By analyzing the interactive storytelling features and innovations of the VR animation <Wolves in the walls>, I hope to summarize the main elements of interactive storytelling from its content. Based on this, I hope to explore how to better showcase interactive storytelling in virtual reality content and provide thoughts on future VR content creation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.253-270
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• 2023

Research on investment determinants of accelerators, which are attracting attention by greatly improving the survival rate of startups by providing professional incubation and investment to startups at the same time, is gradually expanding. However, previous studies do not have a theoretical basis in developing investment determinants in the early stages, and they use factors of angel investors or venture capital, which are similar investors, and are still in the stage of analyzing importance and priority through empirical research. Therefore, this study verified for the first time in Korea the discrimination and effectiveness of investment determinants using accelerator investment determinants developed based on the business model innovation framework in previous studies. To this end, we first set the criteria for success and failure of startup investment based on scale-up theory and conducted a survey of 22 investment experts from 14 accelerators in Korea, and secured valid data on a total of 97 startups, including 52 successful scale-up startups and 45 failed scale-up startups, were obtained and an independent sample t-test was conducted to verify the mean difference between these two groups by accelerator investment determinants. As a result of the analysis, it was confirmed that the investment determinants of accelerators based on business model innovation framework have considerable discrimination in finding successful startups and making investment decisions. In addition, as a result of analyzing manufacturing-related startups and service-related startups considering the characteristics of innovation by industry, manufacturing-related startups differed in business model, strategy, and dynamic capability factors, while service-related startups differed in dynamic capabilities. This study has great academic implications in that it verified the practical effectiveness of accelerator investment determinants derived based on business model innovation framework for the first time in Korea, and it has high practical value in that it can make effective investments by providing theoretical grounds and detailed information for investment decisions.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.189-198
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• 2024

Lipreading is one of the important parts of speech recognition, and several studies have been conducted to improve the performance of lipreading in lipreading systems for speech recognition. Recent studies have used method to modify the model architecture of lipreading system to improve recognition performance. Unlike previous research that improve recognition performance by modifying model architecture, we aim to improve recognition performance without any change in model architecture. In order to improve the recognition performance without modifying the model architecture, we refer to the cues used in human lipreading and set other regions such as chin and cheeks as regions of interest along with the lip region, which is the existing region of interest of lipreading systems, and compare the recognition rate of each region of interest to propose the highest performing region of interest In addition, assuming that the difference in normalization results caused by the difference in interpolation method during the process of normalizing the size of the region of interest affects the recognition performance, we interpolate the same region of interest using nearest neighbor interpolation, bilinear interpolation, and bicubic interpolation, and compare the recognition rate of each interpolation method to propose the best performing interpolation method. Each region of interest was detected by training an object detection neural network, and dynamic time warping templates were generated by normalizing each region of interest, extracting and combining features, and mapping the dimensionality reduction of the combined features into a low-dimensional space. The recognition rate was evaluated by comparing the distance between the generated dynamic time warping templates and the data mapped to the low-dimensional space. In the comparison of regions of interest, the result of the region of interest containing only the lip region showed an average recognition rate of 97.36%, which is 3.44% higher than the average recognition rate of 93.92% in the previous study, and in the comparison of interpolation methods, the bilinear interpolation method performed 97.36%, which is 14.65% higher than the nearest neighbor interpolation method and 5.55% higher than the bicubic interpolation method. The code used in this study can be found a https://github.com/haraisi2/Lipreading-Systems.

• Journal of Global Scholars of Marketing Science
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• v.20 no.2
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• pp.110-122
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• 2010

The emergence of the field of organizational buying behavior in the mid-1960’s with the publication of Industrial Buying and Creative Marketing (1967) set the stage for a new paradigm of thinking about how business was conducted in markets other than those serving ultimate consumers. Whether it is "industrial marketing" or "business-to-business marketing" (B-to-B), organizational buying behavior remains the core differentiating characteristic of this domain of marketing. This paper explores the impact of several dynamic factors that have influenced how organizations relate to one another in a rapidly increasing interdependence, which in turn can impact organizational buying behavior. The paper also raises the question of whether or not the major conceptual models of organizational buying behavior in an interdependent world are still relevant to guide research and managerial thinking, in this dynamic business environment. The paper is structured to explore three questions related to organizational interdependencies: 1. What are the factors and trends driving the emergence of organizational interdependencies? 2. Will the major conceptual models of organizational buying behavior that have developed over the past half century be applicable in a world of interdependent organizations? 3. What are the implications of organizational interdependencies on the research and practice of organizational buying behavior? Consideration of the factors and trends driving organizational interdependencies revealed five critical drivers in the relationships among organizations that can impact their purchasing behavior: Accelerating Globalization, Flattening Networks of Organizations, Disrupting Value Chains, Intensifying Government Involvement, and Continuously Fragmenting Customer Needs. These five interlinked drivers of interdependency and their underlying technological advances can alter the relationships within and among organizations that buy products and services to remain competitive in their markets. Viewed in the context of a customer driven marketing strategy, these forces affect three levels of strategy development: (1) evolving customer needs, (2) the resulting product/service/solution offerings to meet these needs, and (3) the organization competencies and processes required to develop and implement the offerings to meet needs. The five drivers of interdependency among organizations do not necessarily operate independently in their impact on how organizations buy. They can interact with each other and become even more potent in their impact on organizational buying behavior. For example, accelerating globalization may influence the emergence of additional networks that further disrupt traditional value chain relationships, thereby changing how organizations purchase products and services. Increased government involvement in business operations in one country may increase costs of doing business and therefore drive firms to seek low cost sources in emerging markets in other countries. This can reduce employment opportunitiesn one country and increase them in another, further accelerating the pace of globalization. The second major question in the paper is what impact these drivers of interdependencies have had on the core conceptual models of organizational buying behavior. Consider the three enduring conceptual models developed in the Industrial Buying and Creative Marketing and Organizational Buying Behavior books: the organizational buying process, the buying center, and the buying situation. A review of these core models of organizational buying behavior, as originally conceptualized, shows they are still valid and not likely to change with the increasingly intense drivers of interdependency among organizations. What will change however is the way in which buyers and sellers interact under conditions of interdependency. For example, increased interdependencies can lead to increased opportunities for collaboration as well as conflict between buying and selling organizations, thereby changing aspects of the buying process. In addition, the importance of communication processes between and among organizations will increase as the role of trust becomes an important criterion for a successful buying relationship. The third question in the paper explored consequences and implications of these interdependencies on organizational buying behavior for practice and research. The following are considered in the paper: the need to increase understanding of network influences on organizational buying behavior, the need to increase understanding of the role of trust and value among organizational participants, the need to improve understanding of how to manage organizational buying in networked environments, the need to increase understanding of customer needs in the value network, and the need to increase understanding of the impact of emerging new business models on organizational buying behavior. In many ways, these needs deriving from increased organizational interdependencies are an extension of the conceptual tradition in organizational buying behavior. In 1977, Nicosia and Wind suggested a focus on inter-organizational over intra-organizational perspectives, a trend that has received considerable momentum since the 1990's. Likewise for managers to survive in an increasingly interdependent world, they will need to better understand the complexities of how organizations relate to one another. The transition from an inter-organizational to an interdependent perspective has begun, and must continue so as to develop an improved understanding of these important relationships. A shift to such an interdependent network perspective may require many academicians and practitioners to fundamentally challenge and change the mental models underlying their business and organizational buying behavior models. The focus can no longer be only on the dyadic relations of the buying organization and the selling organization but should involve all the related members of the network, including the network of customers, developers, and other suppliers and intermediaries. Consider for example the numerous partner networks initiated by SAP which involves over 9000 companies and over a million participants. This evolving, complex, and uncertain reality of interdependencies and dynamic networks requires reconsideration of how purchase decisions are made; as a result they should be the focus of the next phase of research and theory building among academics and the focus of practical models and experiments undertaken by practitioners. The hope is that such research will take place, not in the isolation of the ivory tower, nor in the confines of the business world, but rather, by increased collaboration of academics and practitioners. In conclusion, the consideration of increased interdependence among organizations revealed the continued relevance of the fundamental models of organizational buying behavior. However to increase the value of these models in an interdependent world, academics and practitioners should improve their understanding of (1) network influences, (2) how to better manage these influences, (3) the role of trust and value among organizational participants, (4) the evolution of customer needs in the value network, and (5) the impact of emerging new business models on organizational buying behavior. To accomplish this, greater collaboration between industry and academia is needed to advance our understanding of organizational buying behavior in an interdependent world.

• 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.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.101-107
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• 2014

With the development of online service, recent forms of databases have been changed from static database structures to dynamic stream database structures. Previous data mining techniques have been used as tools of decision making such as establishment of marketing strategies and DNA analyses. However, the capability to analyze real-time data more quickly is necessary in the recent interesting areas such as sensor network, robotics, and artificial intelligence. Landmark window-based frequent pattern mining, one of the stream mining approaches, performs mining operations with respect to parts of databases or each transaction of them, instead of all the data. In this paper, we analyze and evaluate the techniques of the well-known landmark window-based frequent pattern mining algorithms, called Lossy counting and hMiner. When Lossy counting mines frequent patterns from a set of new transactions, it performs union operations between the previous and current mining results. hMiner, which is a state-of-the-art algorithm based on the landmark window model, conducts mining operations whenever a new transaction occurs. Since hMiner extracts frequent patterns as soon as a new transaction is entered, we can obtain the latest mining results reflecting real-time information. For this reason, such algorithms are also called online mining approaches. We evaluate and compare the performance of the primitive algorithm, Lossy counting and the latest one, hMiner. As the criteria of our performance analysis, we first consider algorithms' total runtime and average processing time per transaction. In addition, to compare the efficiency of storage structures between them, their maximum memory usage is also evaluated. Lastly, we show how stably the two algorithms conduct their mining works with respect to the databases that feature gradually increasing items. With respect to the evaluation results of mining time and transaction processing, hMiner has higher speed than that of Lossy counting. Since hMiner stores candidate frequent patterns in a hash method, it can directly access candidate frequent patterns. Meanwhile, Lossy counting stores them in a lattice manner; thus, it has to search for multiple nodes in order to access the candidate frequent patterns. On the other hand, hMiner shows worse performance than that of Lossy counting in terms of maximum memory usage. hMiner should have all of the information for candidate frequent patterns to store them to hash's buckets, while Lossy counting stores them, reducing their information by using the lattice method. Since the storage of Lossy counting can share items concurrently included in multiple patterns, its memory usage is more efficient than that of hMiner. However, hMiner presents better efficiency than that of Lossy counting with respect to scalability evaluation due to the following reasons. If the number of items is increased, shared items are decreased in contrast; thereby, Lossy counting's memory efficiency is weakened. Furthermore, if the number of transactions becomes higher, its pruning effect becomes worse. From the experimental results, we can determine that the landmark window-based frequent pattern mining algorithms are suitable for real-time systems although they require a significant amount of memory. Hence, we need to improve their data structures more efficiently in order to utilize them additionally in resource-constrained environments such as WSN(Wireless sensor network).

• KOREAN JOURNAL OF CROP SCIENCE
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• v.38 no.1
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• pp.72-84
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• 1993

This study was carried out to understand the varietal variation in physicochemical properties of rice grain and those environmental changes by different transplanting time, and to elucidate the interrelationships among the factors related with eating quality of cooked rice. Fifty three rice samples, among which fifty samples were harvested at ordinary or late transplanted plots of the Crop Experiment Station in Suwon and three samples were harvested orpurchased from Niigata prefecture in Japan, were tested for various physicochemical components of rice grain and some physical factors of cooked rice. All of twenty seven rice cultivars tested were the recent-bred Korean japonica rice showing the wide range of maturity from early to medium-late heading and considerable difference in palatability of cooked rice. Amylose content, taste value by Nireco palatability tester (TVN), iodine blue color of cooking extracts(IB), and the ratio of IB /extracted solid amounts (ES) increased significantly by late transplanting, while viscosity (VN) and Mg / K. N value by Nireco tester, hot-water absorption of milled rice (HA), loss tangent of cooked rice by Rheolograph-Micro(LT), and most viscogram characteristics except setback viscosity (C-P) decreased drastically by late transplanting as compared with ordinary transplanting. Most of physicochemical properties of milled rice revealed narrower varietal variation in lately transplanted plot than in ordinary transplanted one. Protein content (PRO), volume expansion rate of cooked rice(VE), C-P and all physical factors of cooked rice by Rheolograph-Micro showed almost negligible seasonal variation, while amylose content (AM), VN, HA, IB/ES, peak viscosity(P), hot viscosity(H) and breakdown(P-H) viscosity exhibited considerably large seasonal variation. The early-headed varieties revealed lower amylose content and smaller seasonal variation of IB/ES compared with medium or medium-late headed rice varieties. AM was closely associatied with IB and IB / ES and VN was highly correlated with Mg/K. N and TVN in both ordinary and late transplanted plots. VN also was highly negatively correlated with cooking characteristics and highly positively correlated with viscogram properties in ordinary culture. PRO was closely connected with moisture content of milled rice and L T in ordinary transplanted plot. IB, which was closely connected with ES, was also singificantly associated LT, P and P-H in ordinary seasonal culture. IB/ES was highly negatively correlated with P, P-Hand P-H / C-P in ordinary culture but with LT and dynamic viscosity of cooked rice in late seasonal culture. The thirty rice cultivars were largely classified into two varietal groups by cluster analysis with physicochemical properties related with eating quality of cooked rice. Korean and Japanese high-quality rice cultivars were separately distributed in two respective varietal group.

• The Journal of Art Theory & Practice
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• no.9
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• pp.93-121
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• 2010

This study is about Yoo Young-kuk's early works which show constructivism, especially focus on his debut painting, for the 7th Dokuritsu Bijutsu Kyokai(獨立美術協會, the Independent Fine Arts Association) in Tokyo in 1937. The work was painted 2 years after he had started his study in Japan in 1935. It was the first painting that applied Constructivism. played an important role for Constructivism to be a leading art in his abstraction. After this picture, Yoo was soon devoted to the principles of Constructivism-- Faktura(material), Tektonika (tectonics), Tekhnika(technique), space, construction-- in his painterly reliefs. This article examined why Yoo concentrated on Constructivism for , what the characteristics were, and what influences were on other works from 1935 to 1949. In addition, I investigated in which period was painted and how Constructivism was spread in 1930s and early 1940s in chapter 2. I scrutinized Rhapsody in chapter 3. When Yoo created Japan was under the Fifteen Years War(1931-1945), and a major discourse was the Japanese Spirit at that time. It was connected with construction of an ideal nation which the Japanese ultra-national fascism pursued. This ideological pursuit was intended to unite the Japanese people for total war system and to restore a national dignity which had been fallen down due to Manchurian Incident(1931). Thus, on the hand, Kokusai Bunka Shinkokai(國際文化振興, The Society for International Cultural Relations) and the Nippon Kosaku Bunka Renmei(日本工作文化連盟, Japanese Werkbund) were supported financially by the Japanese government. On the other hand, the government enacted regulations to opposing parties which would distract Japanese people's unification. As for the Japanese art world, the merge of art groups was carried out through remodeling of Teikoku Bijutsuin(帝國美術院, The Imperial Fine Arts Academy) in 1935. This brought out continuous dispute and disorder. Young artists who felt difficulty of entering an entry of Imperial Fine Arts Exhibition repeatedly grouped and disbanded for small art groups to build their standing, which they pursued Surrealism and Abstract art. Among them Constructivism was considered as the latest trend and was popular in craft, design, architecture as well as fine arts. In the year before he painted , Avant-garde theatres including Constructivism theatre were introduced in a feature article of September, 1936 in Atelier, which was dealing with mainly avant-garde arts. Books related with Constructivism were translated into Japanese, and Gestaltung Education had become active since the publication of A Compendium of Gestaltung Education("構成敎育大系"(1934)), Salvador Dali(1904-1989) was also introduced, so Surrealism was drawn more attention by young artists. reflected popular trends. Yoo analyzed the Japanese avant-gardists' archaic taste in the Independent Art Association that he submitted his painting to. And then he entitled 'Rhapsody' which derives from Ancient Greek's epic poetry and deliberately set up images in a scene. In chapter 3, I examined a theme which was planned carefully by sorting favorite images from the Japanese Surrealism. was a result that Yoo Young-kuk observed objectively the phenomenon that young artists dreamt of Utopia or longed for Nostalgia passively and lethargically under wars. And then he otherized himself from that circumstance. First of all, for he used the typical icons of Japanese Surrealism such as the horizon, flowing clouds, and vast plain that were considered stereotypes of Arcadia. He, however distinguished himself form those Japanese Surrealists. He made his own vision about Utopia by referring Lyubov Popova(1889-1924)'s stage design. His objective point of view was expressed by positive and dynamic images of structure and human's actions. Constructivism which was attempted in had an effect on other early constructive works, and the principles of Constructivism were sought hard in reliefs, paintings, and photos.