• Journal of Venture Innovation
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• v.7 no.3
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• pp.1-23
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• 2024

This study empirically analyzed the factors affecting acceptance intention when introducing digital transformation in the passenger vehicle transportation business, and examined the moderating effect of corporate agility. Based on the technology acceptance model (TAM) and the technology-organization-environment (TOE) model, the study set introduction usability, ease of introduction, digital transformation capability, CEO support, customer demand, and competitive pressure as independent variables, and 316 effective samples were analyzed by setting corporate agility as a modulating variable. As a result of the analysis, ease of introduction, digital transformation capability, CEO support, customer demand, and competitive pressure all had a significant influence on the intention to accept digital transformation, and in particular, digital transformation capability had the greatest influence. This suggests that the ability of companies to effectively utilize digital technology is an essential factor in the success of digital transformation. On the other hand, the usefulness of introduction did not significantly affect the intention to accept, which means that concerns about costs and risks can have a greater impact on the introduction of digital transformation. In addition, corporate agility showed a positive moderating effect in the relationship between acceptance intention and independent variables, and it was shown that the more agile the company can effectively solve the challenges that arise in the process of introducing digital transformation. In particular, when corporate agility is high, the effect of usefulness of introduction changes positively. This study is the first attempt to systematically analyze digital transformation in the passenger vehicle transportation business, and in practice, it has great academic significance and confirmed the importance of digital transformation capabilities and CEO support. However, since the scope of the study is limited to the passenger vehicle transportation business, there is a limit to generalization, research expanded to various industries and fields is needed in the future.

• Journal of Venture Innovation
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• v.7 no.3
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• pp.45-63
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• 2024

The success of a company in the market is linked to the value it delivers to its customers. However, that value is not always constant. As the environment changes, so do customer experiences and requirements, and eventually the value they seek also evolves. Thus, a timely, clear, and effective value proposition, along with the associated benefits, becomes the functional, psychological, and economic foundation of a business. Therefore, the customer value proposition is crucial in terms of Product-Market Fit (PMF), establishing competitive differentiation, and delivering consistent messaging. Despite this, the most widely known and utilized model related to the Customer Value Proposition (CVP) in general businesses is the Value Proposition Canvas (VPC) by Osterwalder and Pigneur. Apart from that, there are only a few other models used by scholars and experts. In this paper, I selected the VPC model, which is widely used by business practitioners globally, and two other major CVP models well-known to experts. I conducted a detailed analysis of these models and derived the essential elements and key features of a customer value proposition. These were then combined with the Lean Startup methodology, which is frequently used for innovation today, to design an integrated CVP model that startups can easily utilize. The framework proposed in this study is a comprehensive CVP model that incorporates the strengths, weaknesses, characteristics, and commonalities of the three existing CVP models. It is designed to flexibly adapt depending on the business direction or strategic characteristics of the company by comprehensively considering all circumstances of the entire company or a specific product/service. Additionally, it systematically manages the contents of customers' wants & needs, strategic focus, and growth horizons, even after application. The Integrative-Lean CVP Model, designed for easy use by startups, is expected to help them with limited funding and marketing capabilities identify value proposition elements for timely PMF, fostering the creation of a new startup ecosystem.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.121-130
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• 2024

As internet and communication technology (ICT) is improved exponentially, types and amount of available data also increase. Even though data analysis including statistics is significant to utilize this large amount of data, there are inevitable limits to process various and complex data in general way. Meanwhile, there are many attempts to apply machine learning (ML) in various fields to solve the problems according to the enhancement in computational performance and increase in demands for autonomous systems. Especially, data processing for the model input and designing the model to solve the objective function are critical to achieve the model performance. Data processing methods according to the type and property have been presented through many studies and the performance of ML highly varies depending on the methods. Nevertheless, there are difficulties in deciding which data processing method for data analysis since the types and characteristics of data have become more diverse. Specifically, multi-variate data processing is essential for solving non-linear problem based on ML. In this paper, we present a multi-variate tabular data processing scheme for ML-aided data analysis by using Titanic dataset from Kaggle including various kinds of data. We present the methods like input variable filtering applying statistical analysis and normalization according to the data property. In addition, we analyze the data structure using visualization. Lastly, we design an ML model and train the model by applying the proposed multi-variate data process. After that, we analyze the passenger's survival prediction performance of the trained model. We expect that the proposed multi-variate data processing and visualization can be extended to various environments for ML based analysis.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.4
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• pp.225-232
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• 2024

This study focuses on the determination of the fracture mode in composite laminates using deep learning. With the increase in the use of laminated composites in numerous engineering applications, the insurance of their integrity and performance is of paramount importance. However, owing to the complex nature of these materials, the identification of fracture modes is often a tedious and time-consuming task that requires critical domain knowledge. Therefore, to alleviate these issues, this study aims to utilize modern artificial intelligence technology to automate the fractographic analysis of laminated composites. To accomplish this goal, scanning electron microscopy (SEM) images of fractured tensile test specimens are obtained from laminated composites to showcase various fracture modes. These SEM images are then categorized based on numerous fracture modes, including fiber breakage, fiber pull-out, mix-mode fracture, matrix brittle fracture, and matrix ductile fracture. Next, the collective data for all classes are divided into train, test, and validation datasets. Two state-of-the-art, deep learning-based pre-trained models, namely, DenseNet and GoogleNet, are trained to learn the discriminative features for each fracture mode. The DenseNet models shows training and testing accuracies of 94.01% and 75.49%, respectively, whereas those of the GoogleNet model are 84.55% and 54.48%, respectively. The trained deep learning models are then validated on unseen validation datasets. This validation demonstrates that the DenseNet model, owing to its deeper architecture, can extract high-quality features, resulting in 84.44% validation accuracy. This value is 36.84% higher than that of the GoogleNet model. Hence, these results affirm that the DenseNet model is effective in performing fractographic analyses of laminated composites by predicting fracture modes with high precision.

• Journal of Bio-Environment Control
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• v.33 no.1
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• pp.55-62
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• 2024

This study aimed to compare the nutrient uptake rate, growth and yield of strawberry grown under the aquaponic and hydroponic systems in a plant factory. For aquaculture, 12 of fish (Cyprinus carpio cv. Koi) were raised in an aquaponics tank (W 0.7 m × L 1.5 m × H 0.45 m, 472.5 L) filled with 367.5L of water at a density of 5.44 kg·m^-3. The 30 seedlings of strawberry were planted in ports filled with perlite substrate and then were placed on the bed (W 0.7 m × L 1.5 m × H 0.22 m) at the top of the aquaponics system, and the 30 seedlings were planted in net-pots and then placed on the holes of acrylic plates (140 cm × 60 cm, Ø80 mm) on the bed (W 0.7 m × L 1.5 m × H 0.22 m) at the deep flow technique (DFT)- hydroponics. The pH and EC of the aquaponic solution was ranged from 4.3 to 6.9 and 0.32 to 1.14 dS·m^-1, respectively, while those of hydroponics were ranged from 5.1 to 7.5 and 1.0-1.8 dS·m^-1, respectively. The NO₃-N and NH₄-N concentration of the aquaponic solution were higher about 3.6 and 2.2 me·L^-1 than those of the standard hydroponic solution for strawberry cultivation. The P, Ca, Mg, and S ions in the aquaponic solution were also higher about 0.76, 3.1, 0.8, and 0.9 me·L^-1 than those of standard hydroponic solution, respectively, while the K and Fe were lower about 0.8 me·L^-1 and 0.5 mg·L^-1, respectively. The mineral contents of the strawberry leaves grown on aquaponics did not differ from that of hydroponics, and K content in the leaves were in an appropriate range. Uptake rates of T-N and P between the 58 and 98 days after transplant (DAT) were 1.5 and 1.9-fold higher in the aquaponics than those of hydroponics, respectively with no significant difference in the uptake rate of K. The crown diameter, plant height, and leaf length and width in the 98 DAT were significantly higher in aquaponics. The number of fruits per plant was significantly higher in aquaponics than those in hydroponics, and the fresh and dry weights of fruit and length and width of fruit were significantly higher in hydroponics. The results suggest that plants in aquaponics continuously utilize fertilizer components of solid particles from fish and feed wastes.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.4
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• pp.243-254
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• 2024

In recent years, as support for venture companies and performance increase, investment scale increases. To support them goverment operates venture firm confirmation system as a part of a variety of policies. Many studies suggest venture confirmation system offer the practical assistance on performance of venture companies. However, simply venture firm confirmation system affects on performance of venture companies. This study sought to develop a theoretical research model about the impact of innovation capabilities and industrial property rights on venture companies' financial performance and technological capabilities through the venture company confirmation system. The following hypotheses were tested. First, the innovation capabilities of venture companies such as development capability, manufacturing capability, marketing capability, level of cost leadership, level of high added value, degree of clarity of business model, and degree of innovation of business model have a significant impact on the venture company confirmation system. Second, the industrial property rights of venture companies, such as the number of domestic industrial property rights, foreign industrial property rights, industrial property rights in domestic applications, and industrial property rights in overseas applications, do not have a significant impact on the venture business confirmation system. Third, the benefits of the venture business confirmation system, such as promotion of technology development, advertising effects, tax benefits, securing excellent human resources, financing and investment incentives, advantageous participation in government support systems, and deregulation, are related to the financial performance of venture businesses such as sales and operating profit., net profit and technological level. Lastly, it was confirmed that, except for research and development type venture companies, innovation capabilities and industrial property rights do not have a significant impact on financial performance and technological capabilities through the venture confirmation system. The implications of this study mean that in situations where a company's innovation capabilities are lacking, the supply and demand of the venture business confirmation system is weak. Therefore, in order to improve the benefits of the venture business verification system, it is necessary to operate the venture business verification system benefits mainly for companies with high corporate capabilities. Next, it means that industrial property rights are not related to the venture business confirmation system. Therefore, there will be no need to consider industrial property rights as an important matter in the certification of the venture business verification system. Lastly, the higher the level of benefits from the venture business confirmation system, the greater the company's performance and technological capabilities. Therefore, efforts should be made to utilize the venture business verification system in a way that can improve performance or technology through the benefits of the venture business verification system.

• 유학연구
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• v.46
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• pp.53-78
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• 2019

Our leaders and our nation exerted lots of efforts and sacrifices to make rapid change and development of our country in modern times. However, recently their negative images were gradually exposed to us, making our nation have their aspiration for well-conditioned leaders, along with their own responsibilities. For this study, who are good leaders and what are needed for them were deeply thought of. Although there was no clear solution, this study made a premise that the leaders should be nourished to have benevolence, knowledge, bravery and deed, realizing political activities to give our nation satisfactory results. For this, the leaders, for themselves, should make philosophical thoughts for becoming good leaders and for executing their thoughts. However, they are confronted with many problems to do so in real world. Therefore, it is necessary to consistently give them an country-level education for philosophy of leadership for them to form their own philosophical thoughts and to realize their thoughts in our actual lives. One type of method for that can be accomplished through contents of 《Seonghakjipyo》, written by Yulgok Yi yi (李珥, 1536~1584), for the hope of saint king. In this book, he described in details the sayings of the saints and his own thoughts on what should be learnt and practiced for doing self-discipline and ruling the country, adding that it was useful and common to all as well as the leaders. It can be said that this book is very usefulto educate philosophy of leadership for modern leaders, for it is containing the contents both for individuals to learn and practice for restoration of their human nature and for leaders to directly utilize in real political world. This argument may be originated from the fact that the wisdom and the deed needed for good leaders are, in general, all the same, although the system of the great organization like country has been changed. Based on the sections of Self-discipline and Politics in the above book, this study argued the general education for philosophy of leadership. It is focused on definition of education for philosophy of leadership, its meaning in 《Seonghakjipyo》, the reason for using the above book for it, and the suggestion of concrete methods to solve insufficiency of education programs at present for leaders and to execute education for philosophy of leadership that can be practicable in real world. This study showed that the above book could be used for education for philosophy of leadership, arguing that such education could be useful for independently solving many problems both the leaders and our nation might be confronted with in our lives.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.143-163
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• 2016

The demographics of Internet users are the most basic and important sources for target marketing or personalized advertisements on the digital marketing channels which include email, mobile, and social media. However, it gradually has become difficult to collect the demographics of Internet users because their activities are anonymous in many cases. Although the marketing department is able to get the demographics using online or offline surveys, these approaches are very expensive, long processes, and likely to include false statements. Clickstream data is the recording an Internet user leaves behind while visiting websites. As the user clicks anywhere in the webpage, the activity is logged in semi-structured website log files. Such data allows us to see what pages users visited, how long they stayed there, how often they visited, when they usually visited, which site they prefer, what keywords they used to find the site, whether they purchased any, and so forth. For such a reason, some researchers tried to guess the demographics of Internet users by using their clickstream data. They derived various independent variables likely to be correlated to the demographics. The variables include search keyword, frequency and intensity for time, day and month, variety of websites visited, text information for web pages visited, etc. The demographic attributes to predict are also diverse according to the paper, and cover gender, age, job, location, income, education, marital status, presence of children. A variety of data mining methods, such as LSA, SVM, decision tree, neural network, logistic regression, and k-nearest neighbors, were used for prediction model building. However, this research has not yet identified which data mining method is appropriate to predict each demographic variable. Moreover, it is required to review independent variables studied so far and combine them as needed, and evaluate them for building the best prediction model. The objective of this study is to choose clickstream attributes mostly likely to be correlated to the demographics from the results of previous research, and then to identify which data mining method is fitting to predict each demographic attribute. Among the demographic attributes, this paper focus on predicting gender, age, marital status, residence, and job. And from the results of previous research, 64 clickstream attributes are applied to predict the demographic attributes. The overall process of predictive model building is compose of 4 steps. In the first step, we create user profiles which include 64 clickstream attributes and 5 demographic attributes. The second step performs the dimension reduction of clickstream variables to solve the curse of dimensionality and overfitting problem. We utilize three approaches which are based on decision tree, PCA, and cluster analysis. We build alternative predictive models for each demographic variable in the third step. SVM, neural network, and logistic regression are used for modeling. The last step evaluates the alternative models in view of model accuracy and selects the best model. For the experiments, we used clickstream data which represents 5 demographics and 16,962,705 online activities for 5,000 Internet users. IBM SPSS Modeler 17.0 was used for our prediction process, and the 5-fold cross validation was conducted to enhance the reliability of our experiments. As the experimental results, we can verify that there are a specific data mining method well-suited for each demographic variable. For example, age prediction is best performed when using the decision tree based dimension reduction and neural network whereas the prediction of gender and marital status is the most accurate by applying SVM without dimension reduction. We conclude that the online behaviors of the Internet users, captured from the clickstream data analysis, could be well used to predict their demographics, thereby being utilized to the digital marketing.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• The Korean Journal of Quaternary Research
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• v.14 no.1
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• pp.7-31
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• 2000

Quaternary Geological and geophysical investigation was performed at the Eurimji reservoir of Jaechon City in order to interprete depositional environment and genesis of lake sediments. For this purpose, echo sounding, bottom sampling and columnar sampling by drilling on board and GPR survey were employed for a proper field investigation. Laboratory tests cover grain size population analysis, pollen analysis and $^{14}C$ datings for the lake sediments. The some parts of lake bottom sediments anthropogenically tubated and filled several times to date, indicating several mounds on the bottom surface which is difficult to explain by bottom current. Majority of natural sediments were accumulated both as rolling and suspended loads during seasonal flooding regime, when flash flow and current flow are relatively strong not only at bridge area of the western part of Eurimji, connected to stream valley, but at the several conduit or sewage system surrounding the lake. Most of uniform suspend sediments are accumulated at the lake center and lower bank area. Some parts of bottom sediments indicate the existence of turbid flow and mudflow probably due to piezometric overflowing from the lake bottom, the existence of which are proved by CM patterns of the lake bottom sediments. The columnar samples of the lake sediments in ER-1 and ER-3-1 boreholes indicate good condition without any human tubation. The grain size character of borehole samples shows poorly sorted population, predominantly composed of fine sand and muds, varying skewness and kurtosis, which indicate multi-processed lake deposits, very similar to lake bottom sediments. Borehole columnar section, echo sounding and GPR survey profilings, as well as processed data, indicate that organic mud layers of Eurimji lake deposits are deeper and thicker towards lower bank area, especially west of profile line-9. In addition the columnar sediments indicate plant coverage of the Eurimji area were divided into two pollen zones. Arboreal pollen ( AP) is predominant in the lower pollen zone, whreas non-aboreal pollen(NAP) is rich in the upper pollen zone. Both of the pollen zones are related to the vegetation coverage frequently found in coniferous and deciduous broad-leaved trees(mixed forest) surrounded by mountains and hilly areas and prevailing by aquatic or aquatic margin under the wet temperate climate. The $^{14}C$ age of the dark gray organic muds, ER1-12 sample, is 950$\pm$40 years B.P. As the sediments are anthropogenetically undisturbed, it is assumed that the reliability of age is high. Three $^{14}C$ ages of the dark gray organic muds, including ER3-1-8, ER3-1-10, ER3-1-11 samples, are 600$\pm$30 years B.P., 650$\pm$30 years B.P., 800$\pm$40 years B.P. in the descending order of stratigraphic columnar section. Based on the interpretation of depositional environments and formation ages, it is proved that Eurimji reservoir were constructed at least 950$\pm$40 years B.P., the calibrated ages of which ranges from 827 years, B.P. to 866 years B.P. Ancient people utilize the natural environment of the stream valley to meet the need of water irrigation for agriculture in the local valley center and old alluvium fan area.