• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.7
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• pp.1055-1061
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• 2014

Innovative freezing technology is currently applied to preserve foodstuffs for long-term storage. Generally, the quality of frozen food is closely related to the types of freezing and thawing processes. In this study, we characterized the physicochemical properties of onions depending on freezing rate. When onions were frozen at $-40^{\circ}C$, freezing rates were 0.1, 0.5, and $0.7^{\circ}C/min$ depending on air-blast quick freezer mode. Onions were thawed by microwave irradiation at 400 W. Hardness of onion dramatically decreased after freezing and thawing compared with blanched onion. However, the fastest freezing rate did not affect hardness. Thawing loss of onion decreased with a faster freezing rate. For morphological observation, onion frozen at a faster rate showed a smaller ice-crystal size. Vitamin C content decreased upon blanching or freezing, but there was no significant difference according to freezing rate. Although free sugar content also decreased upon blanching and freezing, its highest content was at $0.7^{\circ}C/min$ freezing. Among organic acids, malic acid content was highest at $0.7^{\circ}C/min$ freezing. Based on this study, it could be suggested that a faster freezing rate is effective to improve frozen food quality in accordance with preventing tissue damage or minimizing destruction of nutrients.

• Journal of Korea Technology Innovation Society
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• v.22 no.2
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• pp.207-219
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• 2019

The international trends in activities of government R&D performance measurement is evolving into evidence-based approach to support the verification of objective policy implementation. The European Commission has been implementing KETs (Key Enabling Technologies) policy that incubates nanotech based emerging technologies to support the fourth industrial revolution/revitalization of high-tech manufacturing, and resulting innovations are quantified by KETs Observatory project. The European Commission also built Innovation Radar system that monitors potentially innovative projects within FP7 and Horizon2020 by data analysis. The United States is also upgrading its Federal RePORTER system to quantitatively monitor federal R&D investments with outcomes (including nanotechnology). In the field of Korean nanotechnology, basic statistical data by analyzing NTIS (National Science & Technology Information Service) information is applied in policy field. Developing innovation measurement methodology beyond basic statistical analysis is an international policy issue, and a long-term R&D investment area of a government. The objective of this model study is to quantify the innovation potential of nano R&D investments conducted by Korea government, using input-output based efficiency measurement model and NTIS (National Science & Technology Information Service) that is comprehensive data portal for national R&D investments/outcomes including nanotechnology.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.123-130
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• 2022

Modernization of the educational sector requires globalization, democratization, and the transition to an information technology society. The main goal of education at the present stage is to solve the problem of ensuring the priority of the development of education and science. In modern conditions, the quality of training of qualified specialists is becoming particularly relevant. The great role of teacher education is emphasized by its main goal, which is to train specialists who can ensure the versatile and innovative development of a person as a person and the highest value of society, its mental, physical and aesthetic abilities, high moral qualities, and, consequently, the enrichment on this basis of the intellectual, creative and cultural potential of the people. Among the strategic tasks of modernizing higher education is to ensure informatization of the educational process and access to International Information Systems. The essence of the concept of multimedia is clarified. In the context of media education, multimedia lists a number of functions: informational, interpretive, cultural, entertainment, and educational. The need to meet the needs outlined in the article in the conditions of informatization of the educational process requires the teacher to have knowledge and skills in the field of multimedia pedagogical technologies, knowledge of advanced methods and means of modern science. It is considered what relevant concepts of media education have been developed and are being developed in Ukraine and form an important basis for the modernization of education, which will contribute to the construction of an information society in the country and the formation of civil society. Distance learning is considered - the most democratic form of education that allows broad segments of society to get an education. Distance learning methods are used in higher education institutions, in school education, in the system of advanced training of teachers, in the system of training managerial personnel.

• Convergence Security Journal
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• v.22 no.2
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• pp.115-120
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• 2022

This study analyzed the recent trends in the sports environment to which big data and AI technologies, which are representative technologies of the 4th Industrial Revolution, and approached them from the perspective of convergence of big data and AI technologies in the sports field. And the results are as follows. First, it is being used for player and game data analysis and team strategy establishment and operation. Second, by combining big data collected using GPS, wearable equipment, and IoT with artificial intelligence technology, scientific physical training for each player is possible through user individual motion analysis, which helps to improve performance and efficiently manage injuries. Third, with the introduction of an AI-based judgment system, it is being used for judge judgment. Fourth, it is leading the change in marketing and game broadcasting services. The technology of the 4th Industrial Revolution is bringing innovative changes to all industries, and the sports field is also in the process. The combination of big data and AI is expected to play an important role as a key technology in the rapidly changing future in a sports environment where scientific analysis and training determine victory or defeat.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.969-974
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• 2006

Labor shortages are a serious problem for Korea's construction industry. The problem is both quantitative and qualitative. There is a shortage in supply as due to a decrease in the influx of new labor, and existing workers are less productive as they age. The problem will only get worse as more and more major public projects are being planned. Options for increasing the labor supply are somewhat limited, and thus efforts need to be made to adopt new technologies that can improve the productivity and efficiency of field work and their processes. This paper introduces seven innovation technologies that have the best potential to increase productivity and thus reduce the burden of labor shortage problems. These include 1) Substitution by use of robotics and automation, 2) development and applications of Innovative materials to reduce on site field work, 3) increase in productivity through the implementation of Information Technology, 4) improved productivity through the application of modules, and prefabrication, 5) prevention of rework and redesign, 6) diversification of labor by integrating labor skills, and 7) improved productivity by standardizing site processes.

• Journal of Distribution Science
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• v.10 no.7
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• pp.33-41
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• 2012

The purpose of this study is to analyse the state of the energy industry and to determine the efficiency of its functioning on the basis of energy conservation principle and application of innovative technologies aimed at improving the ecological modernisation of agricultural sectors of Kazakhstan. The research methodology is based on an integrated approach of financial and economic evaluation of the effectiveness of the investment project, based on calculation of elasticity, total costs and profitability, as well as on comparative, graphical and system analysis. The current stage is characterised by widely spread restructuring processes of electric power industry in many countries through introduction of new technical installations of energy facilities and increased government regulation in order to enhance the competitive advantage of electricity market. Electric power industry features a considerable value of creating areas. For example, by providing scientific and technical progress, it crucially affects not only the development but also the territorial organisation of productive forces, first of all the industry. In modern life, more than 90% of electricity and heat is obtained by Kazakhstan's economy by consuming non-renewable energy resources: different types of coal, oil shale, oil, natural gas and peat. Therefore, it is significant to ensure energy security, as the country faces a rapid fall back to mono-gas structure of fuel and energy balance. However, energy resources in Kazakhstan are spread very unevenly. Its main supplies are concentrated in northern and central parts of the republic, and the majority of consumers of electrical power live in the southern and western areas of the country. However, energy plays an important role in the economy of industrial production and to a large extent determines the level of competitive advantage, which is a promising condition for implementation of energy-saving and environmentally friendly technologies. In these circumstances, issues of modernisation and reforms of this sector in Kazakhstan gain more and more importance, which can be seen in the example of economically sustainable solutions of a large local monopoly company, significant savings in capital investment and efficiency of implementation of an investment project. A major disadvantage of development of electricity distribution companies is the prevalence of very high moral and physical amortisation of equipment, reaching almost 70-80%, which significantly increases the operating costs. For example, while an investment of 12 billion tenge was planned in 2009 in this branch, in 2012 it is planned to invest more than 17 billion. Obviously, despite the absolute increase, the rate of investment is still quite low, as the total demand in this area is at least more than 250 billion tenge. In addition, industrial infrastructure, including the objects of Kazakhstan electric power industry, have a tangible adverse impact on the environment. Thus, since there is a large number of various power projects that are sources of electromagnetic radiation, the environment is deteriorated. Hence, there is a need to optimise the efficiency of the organisation and management of production activities of energy companies, to create and implement new technologies, to ensure safe production and provide solutions to various environmental aspects. These are key strategic factors to ensure success of the modern energy sector of Kazakhstan. The contribution of authors in developing the scope of this subject is explained by the fact that there was not enough research in the energy sector, especially in the view of ecological modernisation. This work differs from similar works in Kazakhstan in the way that the proposed method of investment project calculation takes into account the time factor, which compares the current and future value of profit from the implementation of innovative equipment that helps to bring it to actual practise. The feasibility of writing this article lies in the need of forming a public policy in the industrial sector, including optimising the structure of energy disbursing rate, which complies with the terms of future modernised development of the domestic energy sector.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.6
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• pp.47-64
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• 2014

Considering the network externality and spill-over effects, this paper constructs the theoretical model for analyzing the financial policies focusing on the credit guarantee system for Creative Economy, which has been set as the new policy paradigm for the Korean Economy. The analytical results show that it is as much as important to improve the efficiency of the financial markets and construct the infrastructure for reducing the information asymmetry problem which would be more serious in the creative finance. Although it is important to fill the gap due to the market failure it is also crucial to construct the appropriate financial schemes for the various stages of the innovative firms growth. Without these, the impacts of current public funding policies may crowd out the amount of private market funds for the innovative firms or reduce the possibility of commercialization of new technologies in these firms. Based on the evaluation of current related public policies from the perspectives of creative finance, we imply that the current financial policies appear to be quantity oriented not the quality based. Although the policy goals would be appropriately set for vitalizing the Creative Economy in Korea, they appear to be still unsuccessful to address the information asymmetry issue which is the major concern in vitalizing the creative economy. Thus we emphasize the market friendly policies, risk-sharing between the various market participants, revitalizing the relationship banking and efficient management of credit guarantee system in Korea based on the analytical model as well as the evaluation of related policies regarding the creative economy.

• Journal of Korea Technology Innovation Society
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• v.20 no.1
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• pp.175-204
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• 2017

The existing innovation policies and strategies mainly focused on the influencing factors for improvement of innovation outcome. However, these strategies were not always successful in driving innovative activities that make technology innovation disseminated. In this regard, innovation ecosystems approach has recently been coming to the force to establish a successful innovation strategy. The innovation ecosystems concept describes that innovation processes are evolved through collaborative networks of economic actors. In an innovation ecosystem, different organizations collaborate for technology development and its use. They interact for value co-creation by sharing mutual resources. The organizational networks are re-organized by dynamic changes of actors' interactions, which drive innovation mechanism of the networks. Recent studies on innovation ecosystems mostly have paid attention on developing theoretical frameworks to describe dynamics of an innovation ecosystem. There have hardly been empirical tests on the theoretical ecosystem models. In this vein, we investigated dynamics of an innovation ecosystem by analyzing structural characteristics of a collaborative network among organizations which are involved in the use of innovative technologies. Particularly, we examined the longitudinal changes of the interaction patterns among the organizations. This test was performed by an analysis of structural equivalence on the network dataset transformed from the organizational interactions. This result provides a guideline for an organization in developing an innovation strategy under a systemic perspective.

• Journal of Distribution Research
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• v.12 no.2
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• pp.23-49
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• 2007

Recently, mobile marketing is becoming one of the major topics of interest to the marketing discipline. Emerging from rapid developments in mobile technology, it has created opportunities for new and innovative mobile services. Also, it is enabling to conduct always-on connections that consumers can interact anytime and anywhere. Especially, mobile devices place themselves to the core means of mobile-commerce which to execute a function as a distribution channel in mobile environments. Although the adoption researches about innovative services or technologies had executed in marketing areas over the past decades, most researches just expanded or modified existing theories and explanation models. There has been little study on the comprehensive and systematic review of adoption process. Therefore, it deserves to be considered prior usage experiences of the existing channels(CL) and attractiveness of the new channel(CLalt) based on social exchange theory. In order to address this void, this study unifies components of perceived attributes in the each dimensions (ie. benefit, cost, and risk dimensions) and explores prior usage experiences of the existing channels on adoption intention in electronic financial service channels through developing comprehensive model and employing empirical test for the hierarchy of effects model. Based on these empirical results, this study suggests managerial implications for new channel management in electronic financial service areas by focusing on the prior usage experiences of the existing objects on adoption intention and perceived attributes of ubiquitous-based mobile service channel.