• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.4
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• pp.21-29
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• 2023

The Northern Song Dynasty, the heyday of cultural and artistic achievements, brought significant changes to the history of gardens in China. The developments and contemplations that had evolved during the previous Tang Dynasty became intertwined with literature, painting, and art, leading to garden being perceived as works of art. In particular, the emergence of Su Shi(蘇軾) that permeated literature and art during the Northern Song Dynasty, had an impact beyond individual garden creation, influencing the development of public gardens and the diversification of garden. His long exile periods served as an opportunity to understand and reflect the local culture and characteristics, influencing the development of the garden. This study focuses on the ideology of Su Shi(蘇軾) that managed various gardens, examining the relationship between his exlie life and ideology. To do so, the study examines the form of the literati's gardens managed by Su Shi(蘇軾), with a particular emphasis on the Baiheju(白鶴居) garden in Huizhou, revealing the following characteristics and values. First, Su Shi(蘇軾), who was proficient in the Three Houses: Confucianism, Buddhism, and Taoism, combined his philosophy and unique perspective techniques with the location and composition elements of Baiheju(白鶴居) to enjoy the landscape. Although the ancient residence has a simple form, it possesses expansiveness through the combination of internal and external views. The interior is designed to be perceived as a single space, but it allows overlapping experiences of space and simultaneous appreciation of different sceneries. On the other hand, the spatial layout incorporates a hierarchical order to establish a sense of order. Second, the garden reflects the local characteristics, featuring numerous tropical plants and presenting vibrant and contrasting colors with structures. The planting forms embrace the concept of "huosei seikou" (活色生香) to enhance the color harmoniously. Additionally, the garden incorporates the poet's spiritual world, projecting it onto the garden as a contemplative place for spiritual nourishment and exploration of the ideal realm. For the pursuit of serenity and profound contemplation, the selected plantings are simple yet distinctive, providing rhythm and depth to the garden space. Third, Baiheju(白鶴居) has undergone changes over the years, but fundamentally, the form and elements of the garden shaped by Su Shi(蘇軾)'s descendants persist, confirming its heritage value.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.141-158
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• 2023

From the perspective of an entrepreneur, one of the most important factors for understanding the inherent limitations of a startup, reducing the risk of failure, and succeeding is the composition of the talent, that is, the founding team. Therefore, a common concern experienced by entrepreneurs in the pre-entrepreneurship stage or the early stage of startup is the choice between independent startups and co-founding start-up. Nonetheless, in Korea, the share of independent entrepreneurship is significantly higher than that of co-founding start-up. On the other hand, focusing on the fact that many successful global innovative companies are in the form of co-founding start-up, the success factors of co-founding start-up were examined. Most of the related preceding studies are studies that identify the capabilities and characteristics of individual entrepreneurs as factors influencing the survival and success of entrepreneurship, and there is a lack of research on partnerships, that is, co-founding start-up, which are common in the field of entrepreneurship ecosystems. Therefore, this study attempted a multi-case study through in-depth interviews, collection of relevant data, analysis of contextual information, and consideration of previous studies targeting co-founders of domestic startups that succeeded in opportunistic startups. Through this, a model for deriving the phased characteristics and key success factors of co-founding start-up was proposed. As a result of the study, the key element of the preliminary start-up stage was 'opportunity', and the success factors were 'opportunity recognition through entrepreneur's experience' and 'idea development'. The key element in the early stages of start-up is "start-up team," and the success factor is "trust and complement of start-up team," and synergy is shown when "diversity and homogeneity of start-up team" are harmonized. In addition, conflicts between co-founders may occur in the early stages of start-ups, which has a large impact on the survival of start-ups. The conflict between the start-up team could be overcome through constant "mutual understanding and respect through communication" and "clear division of work and role sharing." It was confirmed that the core element of the start-up growth stage was 'resources', and 'securing excellent talent' and 'raising external funds' were important factors for success. These results are expected to overcome the limitations of start-up companies, such as limited resources, lack of experience, and risk of failure, in entrepreneurship studies, and prospective entrepreneurs preparing for a start-up in a situation where the form of co-founding start-up is attracting attention as one of the alternatives to increase the success rate. It has implications for various stakeholders in the entrepreneurial ecosystem.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.185-196
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• 2023

This paper investigates the effects of entrepreneurs' cognitive biases on business opportunity evaluation, given their strong entrepreneurial spirit, which is characterized by innovation, proactivity, and risk-taking. When making decisions related to business activities, entrepreneurs typically make rational judgments based on their knowledge, experience, and the advice of external experts. However, in situations of extreme stress or when quick decisions are required, they often rely on heuristics based on their cognitive biases. In particular, we often see cases where entrepreneurs fail because they make decisions based on heuristics in the process of evaluating and selecting new business opportunities that are planned to guarantee the growth and sustainability of their companies. This study was conducted in response to the need for research to clarify the effects of entrepreneurs' cognitive biases on new business opportunity evaluation, given that the cognitive biases of entrepreneurs, which are formed by repeated successful experiences, can sometimes lead to business failure. Although there have been many studies on the effects of cognitive biases on entrepreneurship and opportunity evaluation among university students and general people who aspire to start a business, there have been few studies that have clarified the relationship between cognitive biases and social networks among entrepreneurs. In contrast to previous studies, this study conducted empirical surveys of entrepreneurs only, and also conducted research on the relationship with social networks. For the study, a survey was conducted using a parallel survey method using online mobile surveys and self-report questionnaires from 150 entrepreneurs of small and medium-sized enterprises. The results of the study showed that 'overconfidence' and 'illusion of control', among the independent variables of entrepreneurs' cognitive biases, had a statistically significant positive(+) effect on business opportunity evaluation. In addition, it was confirmed that the moderating variable, social network, moderates the effect of overconfidence on business opportunity evaluation. This study showed that entrepreneurs' cognitive biases play a role in the process of evaluating and selecting new business opportunities, and that social networks play a role in moderating the structural relationship between entrepreneurs' cognitive biases and business opportunity evaluation. This study is expected to be of great help not only to entrepreneurs, but also to entrepreneur education and policy making, by showing how entrepreneurs can use cognitive biases in a positive way and the influence of social networks.

• Radiation Oncology Journal
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• v.16 no.3
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• pp.311-323
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• 1998

Purpose : Prospective, single arm, Phase I/II clinical trial was performed to assess the efficacy and toxicity of the concurrent chemotherapy and definitive radiotherapy (RT) in patients with previously untreated locally advanced carcinoma of the uterine cervix. Methods and Materials : From Mar 1992 to January 1997, a total of 73 patients with advanced cervical carcinoma were entered on the protocol but 5 patients were excluded in analysis because of patients' refusal of treatment. Their ages ranged from 31 to 77 years, median 58 years. The International Federation of Gynecology and Obstetrics (FIGO) stage distribution was as follows: IIB 46, IIIA 2, IIIB 15 and IVA 5. RT consisted of external beam irradiation to 4,140-5,040 cGy/23-28 fractions plus high dose rate intracavitary treatments to deliver a dose of 30-35 Gy to point A in 6-7 fractions. During the intracavitary treatments parametrial boost was delivered for point B dose of 60 Gy in stage IIB and 65 Gy in stage IIIB. Two cycles of concurrent 5-fluorouracil and cisplatin (FP) chemotherapy (5-fluorouracil 1,000 mg/$m^2$/day continuous infusion for 4 days, day 1-4, 29-32 and cisplatin 20 mg/$m^2$/day intravenous bolus for 3 days day 1-3, 29-31) administered starting on day 1 of RT. Results : The median follow-up was 24 months (range 4-68+). Sixty-four patients were evaluable for survival rate in this protocol: The 5-year actuarial and disease-free survival rate were 52$\%$ and 64$\%$, respectively. The 5-rear actuarial survival for stage IIB and III+IVA patients were 58$\%$ and 36$\%$, respectively The 5-year disease-free survival rate for stage IIB and III+IVA patients were 71$\%$ and 40$\%$, respectively. Of the 68 patients evaluated for patterns of failure, overall recurrence rate was 27.9$\%$ (19/68) : local failure in 5.9$\%$ (4/68), distant metastasis in 10.3$\%$ (7/68) and both in 11.8$\%$ (8/68). Of the 64 patients evaluated for response at one month after the completion of treatment the complete response rate was 78$\%$ (50/64). Concurrent chemoradiation appear to be a well-tolerated regimen but there were two treatment-related deaths. Conclusion : Concurrent chemotherapy of FP with high-dose definitive RT in locally advanced carcinoma of the uterine cervix is feasible and effective with acceptable toxicities. This chemoradiation regimen may offer a modest survival benefit for advanced stage. Further follow-up of these patients will evaluate the impact of this regimen on the long-term local control and their survival.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.35-55
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• 2013

Information technology is a critical resource necessary for any company hoping to support and realize its strategic goals, which contribute to growth promotion and sustainable development. The selection of information technology and its strategic use are imperative for the enhanced performance of every aspect of company management, leading a wide range of companies to have invested continuously in information technology. Despite researchers, managers, and policy makers' keen interest in how information technology contributes to organizational performance, there is uncertainty and debate about the result of information technology investment. In other words, researchers and managers cannot easily identify the independent factors that can impact the investment performance of information technology. This is mainly owing to the fact that many factors, ranging from the internal components of a company, strategies, and external customers, are interconnected with the investment performance of information technology. Using an agent-based simulation technique, this research extracts factors expected to affect investment performance on information technology, simplifies the analyses of their relationship with economic modeling, and examines the performance dependent on changes in the factors. In terms of economic modeling, I expand the model that highlights the way in which product quality moderates the relationship between information technology investments and economic performance (Thatcher and Pingry, 2004) by considering the cost of information technology investment and the demand creation resulting from product quality enhancement. For quality enhancement and its consequences for demand creation, I apply the concept of information quality and decision-maker quality (Raghunathan, 1999). This concept implies that the investment on information technology improves the quality of information, which, in turn, improves decision quality and performance, thus enhancing the level of product or service quality. Additionally, I consider the effect of word of mouth among consumers, which creates new demand for a product or service through the information diffusion effect. This demand creation is analyzed with an agent-based simulation model that is widely used for network analyses. Results show that the investment on information technology enhances the quality of a company's product or service, which indirectly affects the economic performance of that company, particularly with regard to factors such as consumer surplus, company profit, and company productivity. Specifically, when a company makes its initial investment in information technology, the resultant increase in the quality of a company's product or service immediately has a positive effect on consumer surplus, but the investment cost has a negative effect on company productivity and profit. As time goes by, the enhancement of the quality of that company's product or service creates new consumer demand through the information diffusion effect. Finally, the new demand positively affects the company's profit and productivity. In terms of the investment strategy for information technology, this study's results also reveal that the selection of information technology needs to be based on analysis of service and the network effect of customers, and demonstrate that information technology implementation should fit into the company's business strategy. Specifically, if a company seeks the short-term enhancement of company performance, it needs to have a one-shot strategy (making a large investment at one time). On the other hand, if a company seeks a long-term sustainable profit structure, it needs to have a split strategy (making several small investments at different times). The findings from this study make several contributions to the literature. In terms of methodology, the study integrates both economic modeling and simulation technique in order to overcome the limitations of each methodology. It also indicates the mediating effect of product quality on the relationship between information technology and the performance of a company. Finally, it analyzes the effect of information technology investment strategies and information diffusion among consumers on the investment performance of information technology.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.