• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.943-951
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• 2024

This paper considers the simulation-based installation and operation safety analysis of installation and operation machinery of USBL as underwater equipment in operation environments. The simulation model of this mechanical system was developed using flexible multibody dynamics simulation technology. Operation and environmental conditions were applied using dynamic forces model considering ocean environments. The developed simulation model was used to evaluate operation safety through eigenvalue analysis, dynamic forces analysis, and structural analysis. As the analysis results, the operation safety was very low in extreme operation condition due to increase of dynamic loads by VIV effect. It was not a problem because safety factor had more than 2.0 in this case. However, the operation safety should be further strengthened because the USBL and LARS was installed and utilized in unmanned vessel with automatic controls. In order to improve safety by avoiding VIV frequency, we redesigned the USBL pole.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.961-972
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• 2024

As the global elderly population rapidly increases, the mental health of the elderly, particularly depression, has emerged as a significant social issue. This study analyzes the various factors influencing depression in the elderly based on the ICF model. Utilizing data from the Korea Welfare Panel Study, the study identifies the types of changes in depression among individuals aged 65 and older and examines the factors influencing these changes. This longitudinal secondary data analysis research uses the most recent three years of data (2021-2023) from the Korea Welfare Panel. The study sample consisted of 965 elderly individuals, and a latent class growth model was applied to identify the types of depression changes, while a multinomial logistic regression analysis was conducted to analyze the influencing factors. The analysis revealed that elderly depression could be categorized into four types: high-level decrease, high-level maintenance, low-level increase, and low-level maintenance. Main influencing factors included gender, age, education, poverty, social trust, social relationships, participation in economic activities, participation in religious activities, and health status. Particularly, social relationships and health status were significant factors affecting the types of depression changes. To mitigate depression in the elderly, a multifaceted approach considering both individual characteristics and social relationships and health status is required. The study suggests the development of community-based programs and trust-building activities at the community level to maintain and strengthen the social relationships of the elderly. These findings can serve as important foundational data for policies and practices aimed at improving the mental health of the elderly.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.833-840
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• 2024

According to recent data from the Korea Meteorological Administration(KMA), the frequency of typhoons around the Korea Peninsula is almost unchanged, but the intensity is on the rise due to climate change. A typhoon that has become so powerful can cause partial or complete damage to the traffic signal structures, limiting the operation of the vehicle and causing traffic congestion. If the traffic signal structure fails to function properly due to the influence of the typhoon, not only the v ehicle operation will be disrupted, but also direct damage to the traffic signal structure will occur. In addition, if the social overhead cost of traffic congestion is included, the recovery cost caused by the typhoon will increase to an extent that it is difficult to estimate. Therefore, in this study, a wind tunnel experiment was performed by producing a wind tunnel model of an existing fixed traffic signal structure and a traffic signal structure in which signs and traffic lights are hinged. Also, The fixed and hinge structures were modeled as 3D finite elements, and wind-resistant analysis was performed by wind speed, and, wind-resistant safety of traffic signal structures were analyzed and examined through wind-resistant analyses. From the comparative analysis of the results of experiment and FE analysis, it was known that the stress reduction rate of the hinge connection structure was at least 30% compared to that of the fixed connection structure from the results of the wind tunnel experiment and FE analysis. And As a result of finite element analysis for the maximum design wind speed of 50m/s, it was found that the maximum stress generated in the existing structure exceeded all the yield stress, but the maximum stress of the hinge connection structure was within the yield stress. Finally The hinge connection structure showed a relatively large stress reduction rate as the wind speed increased and the length of the lateral beam was shorter at the same wind speed.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.143-159
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• 2017

Due to the rapid development of IT in recent years, not only personal information but also the key technologies and information leakage that companies have are becoming important issues. For the enterprise, the core technology that the company possesses is a very important part for the survival of the enterprise and for the continuous competitive advantage. Recently, there have been many cases of technical infringement. Technology leaks not only cause tremendous financial losses such as falling stock prices for companies, but they also have a negative impact on corporate reputation and delays in corporate development. In the case of SMEs, where core technology is an important part of the enterprise, compared to large corporations, the preparation for technological leakage can be seen as an indispensable factor in the existence of the enterprise. As the necessity and importance of Information Security Management (ISM) is emerging, it is necessary to check and prepare for the threat of technology infringement early in the enterprise. Nevertheless, previous studies have shown that the majority of policy alternatives are represented by about 90%. As a research method, literature analysis accounted for 76% and empirical and statistical analysis accounted for a relatively low rate of 16%. For this reason, it is necessary to study the management model and prediction model to prevent leakage of technology to meet the characteristics of SMEs. In this study, before analyzing the empirical analysis, we divided the technical characteristics from the technology value perspective and the organizational factor from the technology control point based on many previous researches related to the factors affecting the technology leakage. A total of 12 related variables were selected for the two factors, and the analysis was performed with these variables. In this study, we use three - year data of "Small and Medium Enterprise Technical Statistics Survey" conducted by the Small and Medium Business Administration. Analysis data includes 30 industries based on KSIC-based 2-digit classification, and the number of companies affected by technology leakage is 415 over 3 years. Through this data, we conducted a randomized sampling in the same industry based on the KSIC in the same year, and compared with the companies (n = 415) and the unaffected firms (n = 415) 1:1 Corresponding samples were prepared and analyzed. In this research, we will conduct an empirical analysis to search for factors influencing technology leakage, and propose an early warning system through data mining. Specifically, in this study, based on the questionnaire survey of SMEs conducted by the Small and Medium Business Administration (SME), we classified the factors that affect the technology leakage of SMEs into two factors(Technology Characteristics, Organization Characteristics). And we propose a model that informs the possibility of technical infringement by using Support Vector Machine(SVM) which is one of the various techniques of data mining based on the proven factors through statistical analysis. Unlike previous studies, this study focused on the cases of various industries in many years, and it can be pointed out that the artificial intelligence model was developed through this study. In addition, since the factors are derived empirically according to the actual leakage of SME technology leakage, it will be possible to suggest to policy makers which companies should be managed from the viewpoint of technology protection. Finally, it is expected that the early warning model on the possibility of technology leakage proposed in this study will provide an opportunity to prevent technology Leakage from the viewpoint of enterprise and government in advance.

• 한국벤처창업학회:학술대회논문집
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• 2008.04a
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• pp.179-208
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• 2008

In this research, an empirical analysis was performed to determine the correlation between management performance and R&D investment for domestic venture businesses in each industry. Specifically, an empirical analysis for each industry was attempted not only to clarify the general hypothesis on the relationship between management performance and R&D investment for venture businesses but also to demonstrate that differences exist for each industry. Empirical analysis was conducted for eight industries with respect to the $2002{\sim}2006$ panel data extracted as investigative results from the "Investigation Report on Science and Technology R&D Activities" published by the Ministry of Science and Technology. Industrial classification was limited to the middle-level classification (2-digit) in the Korea Standard Industry Code (KSIC) owing to the limited number of panels. Although this research only verified the overall positive effect of R&D activities and funds for existing research on corporate value or productivity and management performance, it was able to document the difference for each individual industry and each business size unlike existing research.Furthermore, the reliability of the research results was enhanced by targeting companies that have been continuously conducting R&D and management activities using consistent 5-year panel data in the analysis. Again, this was something that existing research did not have. Finally, through the use of recent data from 2002 after the IMF economic crisis up to 2006 in the empirical analysis, this research proposed the problems due to the prevailing circumstances at the time of entering the advanced nation stage based on an empirical analysis; the prevailing problems during the pursuit of advanced nation status before the IMF crisis broke out were not tackled. The key empirical analysis yielded several results. First, capital and size of the labor force have a positive correlation with the management performance for the entire company or the venture business. This applies to all eight industries as the subjects of the analysis. Second, although the number of years since a company has been established can have positive or negative correlation with management performance for the entire company or venture business in specific industries, a definite overall trend cannot be identified. Third, R&D investment can be said to have an overall positive effect on corporate management performance. Fourth, the size of the research staff cannot be said to be a factor unilaterally affecting the management performance of the entire company or the venture business. Fifth, the number of years a research institute has been in operation, which was assumed to have a positive effect on the management performance of a company because of the accumulated R&D know-how -- definitely acts as a positive factor contributing to the management performance of a company.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.3 no.1
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• pp.1-28
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• 2008

In this research, an empirical analysis was performed to determine the correlation between management performance and Empirical Research on the R&D investment for domestic venture businesses in each industry. Specifically, an empirical analysis for each industry was attempted not only to clarify the general hypothesis on the relationship between management performance and R&D investment for venture businesses but also to demonstrate that differences exist for each industry. Empirical analysis was conducted for eight industries with respect to the $2002{\sim}2006$ panel data extracted as investigative results from the "Investigation Report on Science and Technology R&D Activities" published by the Ministry of Science and Technology. Industrial classification was limited to the middle-level classification (2-digit) in the Korea Standard Industry Code (KSIC) owing to the limited number of panels. Although this research only verified the overall positive effect of R&D activities and funds for existing research on corporate value or productivity and management performance, it was able to document the difference for each individual industry and each business size unlike existing research. Furthermore, the reliability of the research results was enhanced by targeting companies that have been continuously conducting R&D and management activities using consistent 5-year panel data in the analysis. Again, this was something that existing research did not have. Finally, through the use of recent data from 2002 after the IMF economic crisis up to 2006 in the empirical analysis, this research proposed the problems due to the prevailing circumstances at the time of entering the advanced nation stage based on an empirical analysis; the prevailing problems during the pursuit of advanced nation status before the IMF crisis broke out were not tackled. The key empirical analysis yielded several results. First, capital and size of the labor force have a positive correlation with the management performance for the entire company or the venture business. This applies to all eight industries as the subjects of the analysis. Second, although the number of years since a company has been established can have positive or negative correlation with management performance for the entire company or venture business in specific industries, a definite overall trend cannot be identified. Third, R&D investment can be said to have an overall positive effect on corporate management performance. Fourth, the size of the research staff cannot be said to be a factor unilaterally affecting the management performance of the entire company or the venture business. Fifth, the number of years a research institute has been in operation, which was assumed to have a positive effect on the management performance of a company because of the accumulated R&D know-how -- definitely acts as a positive factor contributing to the management performance of a company.

• 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.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.5
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• pp.843-852
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• 2020

Among the many packaging materials used in cushion packaging, there is a lack of optimum design for packaging trays and cushion pads used in pear packaging for export and domestic distribution. It causes over-packaging due to excessive material input, and can be solved by applying various parameters needed to optimize the design of the packaging tray and cushion pad considering the packaging material and the number of pears in the box. In the case of a cushion pad for pears, the economic efficiency of material and thickness should be considered. Therefore, it is possible to design a packaging tray and cushion pad depending on eco-friendly packaging materials (PLA, PET) used by applying appropriate design parameters. The static characteristics of the materials used for the packaging of pears were analyzed using FEA (finite element analysis) simulation technique to derive the optimal design parameters. In this study, we analyzed the contact stress and deformation of PET, PLA tray (0.1, 0.5 1.0, 1.5 and 2 mm) and PET foam (2.0, 3 .0 and 4.0 mm) with pears to derive appropriate cushion packaging design factors. The contact stress between the pear and PET foam pad placed on PLA, PET trays were simulated by FEA considering the bioyield strength (192.54±28 kPa) of the pears and safety factor (5) of packaging design, which is the criterion of damage to the pears. For the combination of PET tray and PET foam buffer pad, the thickness of the PET foam is at least 3 mm, the thickness of the PET foam is at least 1.0 mm, the thickness of the foam is at least 2 mm, and if the thickness of the PET tray is at least 1.5 mm, the thickness of the foam is at least 1 mm, suitable for the packaging design. In addition, for the combination of PLA tray and PET foam pad, the thickness of the PET foam was not less than 2 mm if the thickness of the PLA tray was 0.5 mm, and 1 mm or more if the thickness of the PLA tray was not less than 1.0 mm, the thickness of the PET foam was suitable for the packaging design.

• Journal of Technology Innovation
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• v.26 no.2
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• pp.129-149
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• 2018

Technology finance is an area in which financial authorities have introduced and implemented a strong policy will for the advancement of the financial industry and the development of SMEs. As a result, the Bank's own technology evaluation was conducted from September 2016. Technically superior companies are upgrading their credit ratings, and as a result, they benefit from financial transactions as much as their higher credit ratings through technology evaluation. Based on the data generated during this process, we analyze the degree to which credit ratings was upgraded by technology evaluation. The pre study handles 406 data from KEB Hana Bank's technology evaluation conducted in the second half of 2016. As a result of combining the credit rating with the calculated technology rating, J58 'Publishing Activities' technology-credit rating is raised by 1.05 rating, which is the highest, and C10 'Manufacture of Food Products' is the second highest. As a result, we were able to identify the sectors that benefited from the technology evaluation and confirmed the usefulness of technology evaluation by industry(KSIC). To expanding the study, 2,719 companies evaluated during the entire period were analyzed by technology grade, business experience and promising growth industry code. As a result of the analysis, technological power over T-4 grade companies had the highest credit rating upgrades. The companies belonging to promising growth industries designated for efficiency of policy support, it is confirm that the support of the promising business type was useful because the credit grade was upgraded through technology evaluation. The validity of the technology evaluation based on the five-year business experience was found to be insignificant. In the future, it will be possible to maximize the support effect by concentration on the companies with over T-4 grade and growth potential companies when supporting SMEs.