• The Journal of Small Business Innovation
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• v.20 no.2
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• pp.17-34
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• 2017

This study examines the role of family involvement and national culture in entrepreneurs' choice of mode of entry into entrepreneurship. Mode of entry consists of two choices: starting a new venture or taking over an existing firm. Specifically, we investigate how cultural values moderate the relationship between family involvement and their choice of business takeover. Using a cross-national sample of 3,831 respondents from 33 countries in Flash Eurobarometer data, we develop key variables and test our hypotheses employing hierarchical linear modelling. Our results show that the relationship between family involvement of entrepreneurs and their choice of business takeover is moderated by individualism, short term orientation, and power distance. This research contributes to understanding comparative international entrepreneurship based on national culture. Implications for policy makers and educators are discussed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.1
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• pp.86-95
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• 2014

Productivity improvement of a shipbuilding company depends on how efficiently its limited resources are managed and utilized. Recently, research on modeling and simulation (M&S) to support shipyard production management system has been being under study. The production management based on M&S rejects decision making on experience, and it can establish productivity improvement method based on quantitative and specific data. In this paper, M&S is applied to the long-term plan as a part of the production planning in shipyards. To this end, the long-term plan processes and related management systems are analyzed. Based on the analysis, a simulation model and an application system using commercial simulation software are suggested. And basic structure of the suggested system is based on web technology such as Rich Internet Application, web services protocol for compatibility with existing shipyard enterprise systems. Utilizing the results of this study, it is expected that shipyard production planners can settle down work flow, in which one can establishes the production plan, simulates the plan, and analyzes the results, enabling a more reliable production plans.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.4 s.316
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• pp.28-35
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• 2007

Airbone laser altimeters have been utilized for 3D topographic mapping of the earth, moon, and planets with high resolution and accuracy, which is a rapidly growing remote sensing technique that measures the round-trip time emitted laser pulse to determine the topography. The traveling time from the laser scanner to the Earth's surface and back is directly related to the distance of the sensor to the ground. When there are several objects within the travel path of the laser pulse, the reflected laser pluses are distorted by surface variation within the footprint, generating multiple echoes because each target transforms the emitted pulse. The shapes of the received waveforms also contain important information about surface roughness, slope and reflectivity. Waveform processing algorithms parameterize and model the return signal resulting from the interaction of the transmitted laser pulse with the surface. Each of the multiple targets within the footprint can be identified. Assuming each response is gaussian, returns are modeled as a mixture gaussian distribution. Then, the parameters of the model are estimated by LMS Method or EM algorithm However, each response actually shows the skewness in the right side with the slowly decaying tail. For the application to require more accurate analysis, the tail information is to be quantified by an approach to decompose the tail. One method to handle with this problem is proposed in this study.

• Journal of the Korea Society of Computer and Information
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• v.18 no.6
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• pp.63-70
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• 2013

In accordance with the advancement of IT, application systems with various and complex functions are being required. Such application systems are typically built based on database in order to manage data efficiently. But most object-oriented analysis design methodologies for developing web application systems have not been providing interconnections with the database. Since the requirements regarding the security issues increased, the importance of security has become emphasized. However, since the security is usually considered at the last step of development, it is difficult to apply the security during the whole process of system development, from the requirement analysis to implementation. Therefore, this paper suggests an object-oriented analysis and design methodology for secure database design from the requirement analysis to implementation. This object-oriented analysis and design methodology for secure database design offers correlations with database that most existing object-oriented analysis and design methodologies could not provide. It also uses UMLsec, the modeling language, to apply security into database design. In addition, in order to implement security, RBAC (Role Based Access Control) of relational database is used.

• Journal of Technology Innovation
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• v.29 no.4
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• pp.1-30
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• 2021

Due to the recent development of system semiconductors, technical innovation for the electric devices of the automobile industry is rapidly progressing. In particular, the electric device of automobiles is accelerating technology development competition among automobile parts makers, and the development cycle is also changing rapidly. Due to these changes, the importance of strategic planning for R&D is further strengthened. Due to the paradigm shift in the automobile industry, the Product-Technical Roadmap (P/TRM), one of the R&D strategies, analyzes technology forecasting, technology level evaluation, and technology acquisition method (Make/Collaborate/Buy) at the planning stage. The product-technical roadmap is a tool that identifies customer needs of products and technologies, selects technologies and sets development directions. However, most companies are developing the product-technical roadmap through a qualitative method that mainly relies on the technical papers, patent analysis, and expert Delphi method. In this study, empirical research was conducted through simulations that can supplement and strengthen the product-technical roadmap centered on the automobile industry by fusing Gartner's hype cycle, cumulative moving average-based data preprocessing, and deep learning (LSTM) time series analysis techniques. The empirical study presented in this paper can be used not only in the automobile industry but also in other manufacturing fields in general. In addition, from the corporate point of view, it is considered that it will become a foundation for moving forward as a leading company by providing products to the market in a timely manner through a more accurate product-technical roadmap, breaking away from the roadmap preparation method that has relied on qualitative methods.

• Conservation Science in Museum
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• v.24
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• pp.55-74
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• 2020

The Sacred Bell of Great King Seongdeok is required digital precision recording of conservation conditions because of corrosion and partial abrasion of its patterns and inscriptions. Therefore, this study performed digital documentation of the bell using four types of scanning and unmanned aerial vehicle (UAV) photogrammetry technologies, and performed the various shape analyses through image processing. The modeling results of terrestrial laser scanning and UAV photogrammetry were merged and utilized as basic material for monitoring earthquake-induced structural deformation because these techniques can construct mutual spatial relationships between the bell and its tower. Additionally, precision scanning at a resolution four to nine times higher than that of the previous study provided highly valuable information, making it possible to visualize the patterns and inscriptions of the bell. Moreover, they are well-suited as basic data for identifying surface conservation conditions. To actively apply three-dimensional scanning results to the conservation of the original bell, the time and position of any changes in shape need to be established by further scans in the short-term. If no change in shape is detected by short-term monitoring, the monitoring should continue in medium- and long-term intervals.

• Knowledge Management Research
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• v.25 no.1
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• pp.43-66
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• 2024

In an era where digital technology reshapes brand-consumer interactions, this study examines the influence of Nike's Run Club and Adidas' Runtastic apps on loyalty and advocacy. Analyzing 3,715 English reviews from January 2020 to October 2023 through text mining, and conducting a focused sentiment analysis on 155 'recommend' mentions, we explore the nuances of 'hot loyalty'. The findings reveal Nike as a 'companion' with an emphasis on emotional engagement, versus Runtastic's 'tool' focus on reliability. This underscores the varied consumer perceptions across similar platforms, highlighting the necessity for brands to integrate user preferences and address technical flaws to foster loyalty. Demonstrating how customized technology adaptations impact loyalty, this research offers crucial insights for digital brand strategy, suggesting a proactive approach in app development and management for brand loyalty enhancement

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."

• Korean Journal of Heritage: History & Science
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• v.46 no.3
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• pp.172-193
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• 2013

This study examines the production techniques and raw materials shown in the Korean dried-lacquer statues of Buddha through a careful observation of the Seated Dried-lacquer Bodhisattva Statue from the late Goryeo Dynasty which is currently possessed by Okura Museum of Art in Tokyo. As a method of study, the X-ray data and the results from a field survey were combined to analyze the production techniques and the characteristics of raw materials. Based on this analysis, a hypothesis was established on the production process and verified through a reenactment of the actual production process. Then, the characteristics of the techniques applied to each process and the raw materials were recorded in detail. Specifically, the dried lacquer techniques and the raw materials were estimated based on the results of naked-eye observation in comparison with the literature, especially the records of "Xiu Shi Lu" written by Huang Cheng of the Ming Dynasty which is considered as 'the textbook of lacquer techniques.' The raw materials used in the production of the traditional Korean lacquerware inlaid with mother-of-pearl were also referenced. As a result, it was found that the features of production techniques and the raw materials found in the Statue at Okura Museum of Art have many similarities with those of the Seated Dried-lacquer Statue of Lohan (Arhat) from Yuanfu 2 Nian Ming (1098) of the Song Dynasty which is currently at the Honolulu Museum of Art. In particular, the similarities include that the interior of the statue being vacant because the clay and the wood core were not replaced after being removed from the prototype, that the complete form was made in the clay forming stage to apply the lacquer with baste fiber fabric, that the clay and the wood core were removed through the bottom of the statue, and that the modeling stage was omitted and the final coat over the statue is very thin. Additionally, decorating with ornaments like Bobal and Youngrak made of plastic material was a technique widely popular in the Song Dynasty, suggesting that the Seated Dried-lacquer Bodhisattva Statue in Okura Museum of Art was greatly affected by the production techniques of the Dried-lacquer Buddha Statue from the Song Dynasty. There is no precise record on the origin and history of the Korean Dried-lacquer Buddha Statues and the number of existing works is also very limited. Even the records in "Xuanhe Fengshi Gaoli Tujing" that tells us about the origin of the Dried-lacquer Buddha Statue from the Yuan Feng Period (1078~1085) do not indicate the time of transmission. It is also difficult to trace the clear route of transmission of production techniques through existing Dried-lacquer Buddha Statues. Fortunately, this study could at least reveal that the existing Dried-lacquer Buddha Statues of Korea, including the one at Okura Museum of Art, have applied the production techniques rather differently from those used in the production of Japanese Datsukatsu Dried-lacquer Buddha Statues that have been known as the standard rule in making dried-lacquer statues of Buddha for a long time.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.53-68
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• 2024

Generative AI is receiving a lot of attention around the world, and ways to effectively utilize it in the business environment are being explored. In particular, since the public release of the ChatGPT service, which applies the GPT-3.5 model, a large language model developed by OpenAI, it has attracted more attention and has had a significant impact on the entire industry. This study focuses on the emergence of Generative AI, especially ChatGPT, which applies OpenAI's GPT-3.5 model, to investigate its impact on the startup industry and compare the changes that occurred before and after its emergence. This study aims to shed light on the actual application and impact of generative AI in the business environment by examining in detail how generative AI is being used in the startup industry and analyzing the impact of ChatGPT's emergence on the industry. To this end, we collected company information of generative AI-related startups that appeared before and after the ChatGPT announcement and analyzed changes in industry, business content, and investment information. Through keyword analysis, topic modeling, and network analysis, we identified trends in the startup industry and how the introduction of generative AI has revolutionized the startup industry. As a result of the study, we found that the number of startups related to Generative AI has increased since the emergence of ChatGPT, and in particular, the total and average amount of funding for Generative AI-related startups has increased significantly. We also found that various industries are attempting to apply Generative AI technology, and the development of services and products such as enterprise applications and SaaS using Generative AI has been actively promoted, influencing the emergence of new business models. The findings of this study confirm the impact of Generative AI on the startup industry and contribute to our understanding of how the emergence of this innovative new technology can change the business ecosystem.