• Journal of the Daesoon Academy of Sciences
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• v.20
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• pp.223-272
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• 2009

Both Daesoon philosophy and Buddhist philosophy have strong aspirations for establishing a world comprised of human-beings. In other words, Daesoon philosophy and Buddhist philosophy put human-beings in the place of 'subject character(主語的 人格)' instead of 'predicate character(述語的 人格).' This is because a human is the master rather than a guest of the universe and the world. In this regard, it is safe to say that both Daesoon philosophy and Buddhist philosophy have a common goal of reaching 'an infinitely open life managed by a human-being, the master.' Daesoon philosophy and Buddhist philosophy also share the idea that everything in the universe is an organistic world that is closely connected, like a network. In this aspect, the two philosophies consider the whole world rather than the individual, and seek ways for people to live together actively while expanding the scope of community to the world. Even if 'the morality of living together (相生)' and 'the realization of mercy(同體大悲)' are completely different languages on the surface, it is not difficult to understand the homogeneity inherent in such expressions. Daesoon philosophy and Buddhist philosophy show endless reliability towards all humans and are declarative and reasonable, but both herald human beings as eligible to become the main characters of the future world and lead to the birth of independent human beings while inducing them to the highest position in the universe by liberating humans from the limitations they find. 'Heaven on Earth' as stated in Daesoon philosophy refers to an ideal society where humans and God harmonize, and God and humans complement each other. Also, the world will achieve political stability and equality, realizing an economically prosperous world. Furthermore, social justice will be realized and cultural and religious conflicts resolved. As humans acknowledge there is a way to live together in a universal nature, the environmental issue no longer becomes the top priority for human beings and a world where the morals of human beings reach the highest level will be established. From the original Buddhist perspective, King Jeonrhyun, the proxy of Buddha, realizes the ideal of Buddhism in the mundane world. The world controlled by King Jeonrhyun can be described as having liberty, equality, peace, justice, prosperity, morality, order, legality, democracy, welfare, etc. Therefore, the ideal Buddhist world is materially prosperous, physically healthy and socially just, as well as a world where moral maturity and mental freedom are achieved.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.67-76
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• 2023

Although deep learning models are making innovative achievements in the field of computer vision, the problem of vulnerability to adversarial examples continues to be raised. Adversarial examples are attack methods that inject fine noise into images to induce misclassification, which can pose a serious threat to the application of deep learning models in the real world. In this paper, we propose a model that detects adversarial examples using differences in predictive values between edge-learned classification models and underlying classification models. The simple process of extracting the edges of the objects and reflecting them in learning can increase the robustness of the classification model, and economical and efficient detection is possible by detecting adversarial examples through differences in predictions between models. In our experiments, the general model showed accuracy of {49.9%, 29.84%, 18.46%, 4.95%, 3.36%} for adversarial examples (eps={0.02, 0.05, 0.1, 0.2, 0.3}), whereas the Canny edge model showed accuracy of {82.58%, 65.96%, 46.71%, 24.94%, 13.41%} and other edge models showed a similar level of accuracy also, indicating that the edge model was more robust against adversarial examples. In addition, adversarial example detection using differences in predictions between models revealed detection rates of {85.47%, 84.64%, 91.44%, 95.47%, and 87.61%} for each epsilon-specific adversarial example. It is expected that this study will contribute to improving the reliability of deep learning models in related research and application industries such as medical, autonomous driving, security, and national defense.

• Journal of Venture Innovation
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• v.6 no.1
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• pp.115-137
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• 2023

This study analyzed the relationship between organizational innovative capability and absorptive capacity, market and technology orientations, and their impact on business performance for IT-BPO companies that are required to absorb new technologies from a leading perspective in the digital transformation era. To achieve this, an online specialized research company and offline surveys were conducted on 291 domestic IT-BPO companies, and SPSS 23 was used for descriptive statistics and reliability analysis while AMOS 23 was used for hypothesis testing including validity and mediating effects. The main findings were as follows: First, in the relationship between innovation and absorptive capabilities and Market Orientation Strategic(MOS), learning capability and knowledge network capability were found to have a statistically significant positive (+) effect on MOS. In the relationship between innovation and absorptive capabilities and Technology Orientation Strategic(TOS), R&D capability, potential absorptive capacity, and realized absorptive capacity had a statistically significant positive (+) effect on TOS. Second, in the relationship between innovation and absorptive capabilities and BP, only R&D capability was found to have a significant effect on BP. Third, both market orientation and technology orientation were found to have a significant positive (+) effect on BP. These findings suggest that effective competency factors can be identified according to the market and technology orientations pursued by IT-BPO companies to increase their growth and value creation, and provide implications for developing differentiated competency enhancement strategies based on strategic objectives.

• Journal of Family Resource Management and Policy Review
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• v.27 no.3
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• pp.1-19
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• 2023

This study aims to develop a family strength scale for dual-earner families with young children. Based on existing theories of family strength and a review of related literature, we draw on 80 items to measure the strength of dual-earner families. Using a sample of 747 people, all members of dual-earner families with young children, we examined the items' factor structures. Using the statistical method, we checked the validity and reliability of these items. The final scale consisted of four domains with a total of 49 items : basic foundation (basic structure, economic life, and resource management), parenting, social interest and participation (citizenship, volunteer, leisure, network), work-life balance (balance between work and family, sharing the family role, equal division of role). The developed scale can be used in the field, such as in the Healthy Family Support Center or Family Center, in the context of education, counseling, or consulting for dual-earner families. In order to enhance the usefulness and efficiency of the scale, the adequate education system for the professionals who handle this scale in the field and updated data are required.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.31-47
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• 2022

The TIPS, a representative public-private cooperative project to revitalize the start-up ecosystem, is a government supported policy that promotes successful commercialization through various start-up support for technology-based startups. The purpose of this study is to analyze the investment decision factors of the TIPS program and to derive priorities. In order to achieve the research purpose, first, the investment decision factors were derived through literature analysis, a Delphi surveys were conducted on investors and experts participating in the evaluation of the TIPS program, and an AHP analysis was conducted on 20 VCs to empirically analyze the priority of factors on investment decisions. As a result of the analysis, the importance of critical factors was confirmed in the order of entrepreneurs(team) > market > product/service > finance > network. The importance of detailed factors was found in the order of entrepreneur's reliability and authenticity > market growth and scalability > team members' expertise and capabilities > adequacy of current market size > new market creation. This study presented the capabilities of technology-based startups preparing to participate in the TIPS program by deriving factors that influence investment decisions from an investor's perspective and comparing and analyzing the importance. It is also meaningful that basic data on determinants of private-led investment decision-making were presented to stake-holders such as venture capital, accelerator, and start-up support institutions.

• Journal of The Korean Association For Science Education
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• v.27 no.1
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• pp.93-104
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• 2007

The purpose of this study is to investigate brain activity both during the processing of a scientific hypothesis about biological phenomena and mental arithmetic using 3.0T fMRI at the KAIST. For this study, 16 healthy male subjects participated voluntarily. Each subject's functional brain images by performing a scientific hypothesis task and a mental arithmetic task for 684 seconds were measured. After the fMRI measuring, verbal reports were collected to ensure the reliability of brain image data. This data, which were found to be adequate based on the results of analyzing verbal reports, were all included in the statistical analysis. When the data were statistically analyzed using SPM2 software, the scientific hypothesis generating process was found to have independent brain network different from the mental arithmetic process. In the scientific hypothesis process, we can infer that there is the process of encoding semantic derived from the fusiform gyrus through question-situation analysis in the pre-frontal lobe. In the mental arithmetic process, the area combining pre-frontal and parietal lobes plays an important role, and the parietal lobe is considered to be involved in skillfulness. In addition, the scientific hypothesis process was found to be accompanied by scientific emotion. These results enabled the examination of the scientific hypothesis process from the cognitive neuroscience perspective, and may be used as basic materials for developing a learning program for scientific hypothesis generation. In addition, this program can be proposed as a model of scientific brain-based learning.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.31-41
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• 2024

Deep learning models show excellent performance in tasks such as image classification and object detection in the field of computer vision, and are used in various ways in actual industrial sites. Recently, research on improving robustness has been actively conducted, along with pointing out that this deep learning model is vulnerable to hostile examples. A hostile example is an image in which small noise is added to induce misclassification, and can pose a significant threat when applying a deep learning model to a real environment. In this paper, we tried to confirm the robustness of the edge-learning classification model and the performance of the adversarial example detection model using it for adversarial examples of various algorithms. As a result of robustness experiments, the basic classification model showed about 17% accuracy for the FGSM algorithm, while the edge-learning models maintained accuracy in the 60-70% range, and the basic classification model showed accuracy in the 0-1% range for the PGD/DeepFool/CW algorithm, while the edge-learning models maintained accuracy in 80-90%. As a result of the adversarial example detection experiment, a high detection rate of 91-95% was confirmed for all algorithms of FGSM/PGD/DeepFool/CW. By presenting the possibility of defending against various hostile algorithms through this study, it is expected to improve the safety and reliability of deep learning models in various industries using computer vision.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.437-447
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• 2023

By actively adopting technologies from the Fourth Industrial Revolution, the port industry is trending toward new types of ports, such as automated and smart ports. However, behind the development of these ports, there is an increasing risk of cyber security incidents and threats within ports and container terminals, including information leakage through cargo handling equipment and ransomware attacks leading to disruptions in terminal operations. Despite the necessity of research to enhance cyber security within ports, there is a lack of such studies in the domestic context. This study focuses on Busan Port, a representative port in South Korea that actively incorporates technology from the Fourth Industrial Revolution, in order to discover variables for improving cyber security in container terminals. The research results categorized factors for enhancing cyber security in Busan Port's container terminals into network construction and policy support, standardization of education and personnel training, and legal and regulatory factors. Subsequently, multiple regression analysis was conducted based on these factors, leading to the identification of detailed factors for securing and enhancing safety, reliability, performance, and satisfaction in Busan Port's container terminals. The significance of this study lies in providing direction for enhancing cyber security in Busan Port's container terminals and addressing the increasing incidents of cyber security attacks within ports and container terminals.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.2
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• pp.201-219
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• 2014

The Republic of Korea in the real economy to a knowledge economy, and a center of creativity and imagination in the creative economy is changing the paradigm. As the core of creating economic, creative industries with the technology and information play an important role in the industry individuals. In order to solve the problem of the polarization of the economy and high youth unemployment rate of Korea, to recognize the role of the creative industries, as objection part, dimensions pan-national and one creative companies in industries of Mobile Apps various policies that support has been promoted. Support these policies to be able to contribute to the establishment of the success of mobile apps one-person creating company, we performed this study targeting one-person company that creates mobile apps area, we conducted a demonstration study of success factors, and thus more effective and efficient in an attempt to seek out support measures. In this study, we derive a research 4 hypothesis about the success factors of one creative enterprise through literature discussion, a study was made on the basis of empirical data of one-person company that creates mobile apps. The results of the analysis, first, if the development rate of the mobile application technology is fast and a new competition associated product is appeared, it was possible to find a tendency to be higher at the performance quantitative companies. Second, if the founder is a founding for the benefit and rewarding work and come to terms with the risk, it was possible to discover tends to be higher achievement quantitative. Third, if one-person company select a target market with capture intensively, it was possible to find a tendency for higher qualitative results. Fourth, it could be found that the reliability of the contact frequency of the network related performance business environment these characteristics enterprise management strategy and act as a significant modulatory effect. Provision of information relating to management and entrepreneurship education to be one creative enterprise is required, these results suggest that there is a provision continuing need for the opportunity to be able to meet and network and reliable variety have. In this study, to take advantage to promote the elimination measures that can increase the likelihood of success of the company of institutions to support one company that creates knowledge-based, such as in the field of mobile application.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.421-430
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• 2004

Clinically, it is almost impossible for a physician to distinguish subtle changes of frequency spectrum by using a stethoscope alone especially in the early stage of thrombus formation. Considering that reliability of mechanical valve is paramount because the failure might end up with patient death, early detection of valve thrombus using noninvasive technique is important. Thus the study was designed to provide a tool for early noninvasive detection of valve thrombus by observing shift of frequency spectrum of acoustic signals with computer aid diagnosis system. A thrombus model was constructed on commercialized mechanical valves using polyurethane or silicon. Polyurethane coating was made on the valve surface, and silicon coating on the sewing ring of the valve. To simulate pannus formation, which is fibrous tissue overgrowth obstructing the valve orifice, the degree of silicone coating on the sewing ring varied from 20％, 40％, 60％ of orifice obstruction. In experiment system, acoustic signals from the valve were measured using microphone and amplifier. The microphone was attached to a coupler to remove environmental noise. Acoustic signals were sampled by an AID converter, frequency spectrum was obtained by the algorithm of spectral analysis. To quantitatively distinguish the frequency peak of the normal valve from that of the thrombosed valves, analysis using a neural network was employed. A return map was applied to evaluate continuous monitoring of valve motion cycle. The in-vivo data also obtained from animals with mechanical valves in circulatory devices as well as patients with mechanical valve replacement for 1 year or longer before. Each spectrum wave showed a primary and secondary peak. The secondary peak showed changes according to the thrombus model. In the mock as well as the animal study, both spectral analysis and 3-layer neural network could differentiate the normal valves from thrombosed valves. In the human study, one of 10 patients showed shift of frequency spectrum, however the presence of valve thrombus was yet to be determined. Conclusively, acoustic signal measurement can be of suggestive as a noninvasive diagnostic tool in early detection of mechanical valve thrombosis.