• Radiation Oncology Journal
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• v.19 no.2
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• pp.100-106
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• 2001

Purpose : We performed a retrospective analysis to compare short term results of induction chemotherapy-radiotherapy versus concurrent chemo-radiotherapy in patients with locally advanced nasopharyngeal carcinoma. Materials and Methods : From Oct. 1989 to May 1998, 62 patients with locally advanced nasopharyngeal carcinoma were treated with induction chemotherapy followed by radiotherapy (induction group) or concurrent chemo-radiotherapy (concurrent group). Induction chemotherapy was done for 50 patients, and concurrent chemotherapy for 12 patients. Age, sex, performance status, and pathologic types were evenly distributed between two groups. Stage distribution showed $32\%$ with IIB, $32\%$ with III, and $38\%$ with IV in induction group, and $50\%,\;33.3\%,\;and\;16.7\%$ in concurrent group, respectively. Chemotherapy regimen was CF (cisplatin and 5-FU) in both groups, and drug delivery method also same. Cisplatin $100\;mg/m^2$ was intravenously infused on day 1, and 5-FU $1,000\;mg/m^2$ on day $2\~6$. This was repeated at 3 weeks interval. At the end of radiotherapy, total cycles of chemotherapy were $1\~3$ (median 2) in both groups. Conventionally fractionated radiotherapy with daily fraction size $1.8\~2.0\;Gy$ and 5 fractions/week was done. Total dose was $69.4\~86\;Gy$(median 73.4 Gy) for induction group, and $69.4\~75.4\;Gy$ (median 70.8 Gy) for concurrent group. Follow-up time was $9\~116$ months (median 40.5 months) for induction group, $14\~29$ months (median 21 months) for concurrent group, respectively. Results : Overall 2 year survival rate (2YSR) for all patients was $78.7\%$. According to treatment modality, 2YSR were $77\%$ for induction group, $87\%$ for concurrent group (p>0.05). 2 year disease-free survival rate were $56\%$ and $81\%\;(p>0.05)$, respectively. Complete response to treatment were $75.5\%$ for induction group and $91.7\%$ for concurrent group, but there was no statistical difference. The incidence of grade $3\~4$ hematologic toxicity during radiotherapy was not differ between two groups, but grade 2 leukopenia was more frequent in concurrent group $(18\%\;vs\;66.7\%)$Grade $3\~4$ mucositis was more frequent in concurrent group $(4.0\%\;vs\;33.3\%)$. Overall incidence of grade $3\~4$ acute toxicity during radiotherapy was more frequent in concurrent group $(6.0\%\;vs\;41.7\%,\;p=0.005)$. Conclusion : Concurrent chemo-radiotherapy showed a trend of improvement in short-term survival and in treatment response when compared with induction chemotherapy-radiotherapy in locally advanced nasopharyngeal carcinoma. More controlled randomized trial are needed.

• 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.

• Radiation Oncology Journal
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• v.17 no.3
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• pp.195-202
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• 1999

Purpose : We peformed this study to evaluate the prognostic factors and the effect of induction chemotherapy in locally advanced non-small cell lung cancer (NSCLC). Materials and Methods : A retrospective analysis was done for 130 patients with locally advanced NSCLC treated with curative radiotherapy alone or induction chemo-radiotherapy from January 1986 to October 1996. Eighty-five patients were treated with radiotherapy alone, forty-five with induction chemotherapy and radiotherapy. Age, sex, performance status, histopathologic type, and stage were evenly distributed in both groups. The patients were treated with 6 MV or 10 MV X-ray. Conventional fractionation with daily fraction size 1$.8\~2.0$ Gy was done. Of the patients, 129 patients received total dose above 59.6 Gy ($56\~66$ Gy, median 60 Gy). Induction chemotherapy regimen were CAP (Cyclo-phosphamide, Adriamycin, Cisplatin) in 6 patients, MVP (Mitomycin, Vinblastine, Cisplatin) in 9 patients, MIC (Mitomycin, Ifosfamide Cisplatin) in 13 patients, and EP (Etoposide, Cisplatin) in 17 patients. Chemotherapy was done in $2\~5$ cycles (median 2). Results : Overall 1-, 2-, and 3-year survival rate (YSR) for all patients were $41.5\%,{\;}13.7\%,{\;}and{\;}7\%$, respectively (median survival time 11 months). According to treatment modality, median survival time, overall 1-, 2-, and 3-YSR were 9 months, $32.9\%,{\;}10.\5%,{\;}6\%$ for radiotherapy alone group, and 14 months, $57.8\%,{\;}20\%,{\;}7.6\%$ for induction chemotherapy group, respectively (f=0.0005). Complete response (CR) to overall treatments was $25\%$ (21/84) in radiotherapy alone and $40.5\%$ (17/42) in induction chemotherapy group (p=0.09). The Prognostic factors affecting overall survival were hemoglobin level (p=0.04), NSE (neuron-specific enolase) level (p=0.004), and respense to overall treatment(p=0.004). According to treatment modalities, NSE (neuron-specific enolase) (p=0.006) and response to overall treatment (p=0.003) were associated with overall survival in radiotherapy alone group, and response to overall treatment (p=0.007) in induction chemotherapy group. The failure Pattern analysis revealed no significant difference between treatment modalities. But, in patients with CR to overall treatment, distant metastasis were found in 11/19 patients with radiotherapy alone, and 3/13 patients with induction chemotherapy and radiotherapy (p=0.07). Locoregional failure patterns were not different between two groups (10/19 vs 6/13). Conclusion : Induction chemotherapy and radiotherapy achieved increased 2YSR compared to radiotherapy alone, At least in CR patients, there was decreased tendency in distant metastasis with induction chemotherapy. But, locoregional failures and long-term survival were not improved. Thus, there is need of more effort to increasing local control and further decreasing distant metastasis.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.127-147
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• 2020

The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.1
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• pp.40-53
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• 2015

To train the manpower to meet the requirements of the industrial field, the introduction of the National Qualification Frameworks(hereinafter referred to as NQF) was determined in 2001 by National Competency Standards(hereinafter referred to as NCS) centrally of the Office for Government Policy Coordination. Also, for landscape architecture in the construction field, the "NCS -Landscape Architecture" pilot was developed in 2008 to be test operated for 3 years starting in 2009. Especially, as the 'realization of a competence-based society, not by educational background' was adopted as one of the major government projects in the Park Geun-Hye government(inaugurated in 2013) the NCS system was constructed on a nationwide scale as a detailed method for practicing this. However, in the case of the NCS developed by the nation, the ideal job performing abilities are specified, therefore there are weaknesses of not being able to reflect the actual operational problem differences in the student level between universities, problems of securing equipment and professors, and problems in the number of current curricula. For soft landing to practical curriculum, the process of clearly analyzing the gap between the current curriculum and the NCS must be preceded. Gap analysis is the initial stage methodology to reorganize the existing curriculum into NCS based curriculum, and based on the ability unit elements and performance standards for each NCS ability unit, the discrepancy between the existing curriculum within the department or the level of coincidence used a Likert scale of 1 to 5 to fill in and analyze. Thus, the universities wishing to operate NCS in the future measuring the level of coincidence and the gap between the current university curriculum and NCS can secure the basic tool to verify the applicability of NCS and the effectiveness of further development and operation. The advantages of reorganizing the curriculum through gap analysis are, first, that the government financial support project can be connected to provide quantitative index of the NCS adoption rate for each qualitative department, and, second, an objective standard is provided on the insufficiency or sufficiency when reorganizing to NCS based curriculum. In other words, when introducing in the subdivisions of the relevant NCS, the insufficient ability units and the ability unit elements can be extracted, and the supplementary matters for each ability unit element per existing subject can be extracted at the same time. There is an advantage providing directions for detailed class program and basic subject opening. The Ministry of Education and the Ministry of Employment and Labor must gather people from the industry to actively develop and supply the NCS standard a practical level to systematically reflect the requirements of the industrial field the educational training and qualification, and the universities wishing to apply NCS must reorganize the curriculum connecting work and qualification based on NCS. To enable this, the universities must consider the relevant industrial prospect and the relation between the faculty resources within the university and the local industry to clearly select the NCS subdivision to be applied. Afterwards, gap analysis must be used for the NCS based curriculum reorganization to establish the direction of the reorganization more objectively and rationally in order to participate in the process evaluation type qualification system efficiently.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.55-78
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• 2021

Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.

• Sim-seong Yeon-gu
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• v.38 no.1
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• pp.112-160
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• 2023

This study examined the Korean folklore "Borrowed Fortune from Heaven" from the perspective of Analytical Psychology, considering it a manifestation of the human psyche, and tried to gain a deeper understanding of what happens in our mind. Through the exploration, the researcher was able to re-identify the ongoing psychological process operating in the depths of our mind, pertaining to the emergence of a new dimension of consciousness. Particularly the researcher was able to gain some insights into how the potential psychic elements for the new consciousness are prepared in the unconscious, how they get integrated into the conscious life, and what is essential for the accomplishment of the process. The tale begins with a poor woodcutter who, in order to escape from poverty, starts gathering twice as much firewood. However, the newly acquired amount disappears overnight, so the woodcutter gets perplexed and curious about where it goes and who is taking it. He seeks to find out the truth, which leads him to an unexpected journey to Heaven. There he learns the truth concerning his very tiny amount of fortune, and discovers another big fortune for an unborn person. By pleading with the ruler of Heaven, the woodcutter borrows that grand fortune, on the condition that he must return it to the owner when the time comes. After that, the woodcutter's life undergoes a series of changes, in which he finally becomes a wealthy farmer, but gradually is reminded more and more that the destined time is approaching. In the end, the fortune is completely transferred to the original owner, resulting in a dramatic twist and the creation of a new life circumstances. The overall plot can be understood as a reflection of the psychological process aiming at the evolution of consciousness through renewal. In this context, the woodcutter can be considered a psychic element that undergoes a continuous transformation in preparation for participating in the upcoming new consciousness. In other words, the changes brought about by this figure can be interpreted as a gradual and increasingly detailed foreshadowing of what the forthcoming new consciousness would be like. Interestingly, as the destined time approaches, the protagonist's anguish in conflict reaches its climax, despite his good performance in his role until then. This effectively portrays the difficulty of achieving a new dimension of consciousness, which requires moving past the last step. All the events in the story ultimately converge at this point. After all, the resolution occurs when the protagonist lets go of everything he has and follows the will of Heaven. This implies what is essential for the renewal of consciousness. Only by completely complying with the entire mind, the potential constituents of the new consciousness that should play important roles in a renewal and evolution of consciousness through experiencing, can participate in the ultimate outcome. As long as they remain trapped in any intermediate stage, the totality of the psyche would develop another detour aiming at the final destination, which means the beginning of another period of suffering carrying a purposeful meaning. The tale suggests that this truth will be applied everywhere that renewal of consciousness is directed, whether for an individual or a society.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.