• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.117-130
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• 2019

After Marx, the issues regarding human labour have been the alienation towards production means and the distributive justice. Fourth industrial revolution and development of AI(Artificial Intelligence) opened the possibility of a independent production and economy system absolutely excluding against human nature and labour. Using robots and AI will deepen demarcation between living things and one not having life, separating the intelligence from the consciousness. At present, so called pre-stage of post human, seeking interests for life, new social relationship and new community will be increased as well. We can understand that interests for small community, self-sufficiency, dailiness, food and body in this context is increasing too. Representative trend towards this cultural phenomena is called as the 'Kinfolk culture.' Work-life balance, 'Aucalme', 'Hygge', 'So-Hwak-Haeng'(a small but reliable happiness) are the similar culture trends as. Vital capitalism, presented by O-Yong Lee, seeks focusing onto living things principles, e.g. 'topophilia', 'neophilia', and 'biophilia' as the dynamics looking for the history substructure, not class struggle and conflicts. He also argues the 'Vital Capitalism' be regarded as a new methodology to anticipate a social system after post human era. G. Deleuze said "arts is another expression method for existential philosophy. It gives a vitality onto philosophy and gives a role to letting abstract concept into definite image." We can find a lot cases arts' imagination overcomes critical point of scientific prediction power in the future prediction. This paper reviews ideas and issues of 'vital capitalism' in detail and explorers imaginating initial ideas of vital capitalism in the film 'Little Forest.'

• Journal of Adhesion and Interface
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• v.24 no.3
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• pp.95-99
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• 2023

In this study, LiDAR-detectable black materials are synthesized by coating and reduction of titanium dioxide onto plate-type natural mica, which evaluated practical LiDAR verification. In detail, black TiO₂@Mica materials are fabricated by utilizing a sol-gel reaction to coat titanium dioxide onto natural mica, followed by reduction using sodium tetrahydridoborate. Subsequently, Black TiO₂@Mica materials are dispersed in hydrophilic transparent varnish and sprayed onto the glass substrate to assess applicability as paints. As a result, Black TiO₂@Mica-based paints exhibit true blackness (L^*=12.1) and a higher NIR reflectance (30.2 R%). In addition, it was confirmed that as-synthesized Black TiO₂@Mica materials are successfully recognized by a LiDAR sensor. This phenomenon is attributed to Fresnel's reflection law, in which light reflection occurs at the interface between natural mica and titanium dioxide with different refractive indices. In this regard, the findings of the study are expected to contribute to the potential utilization of LiDAR-detectable materials in various fields such as autonomous vehicles, robotics, and drones.

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.9-18
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• 2023

Climate change affects the safety of river revetments, especially those associated with external flooding. Research on slope reinforcement has been actively conducted to enhance revetment safety. Recently, technologies for producing embankment blocks using recycled materials have been developed. However, it is essential to analyze the impact of block shapes on the flow characteristics of exclusion zones for revetment safety. Therefore, this study investigates the influence of revetment block shapes on the hydraulic characteristics of revetment surfaces through 3D numerical simulations. Three block shapes were proposed, and numerical analyses were performed by installing the blocks in an idealized river channel. FLOW-3D was used for the 3D numerical simulations, and the variations in maximum flow velocity, bed velocity beneath the revetment, and maximum shear stress were analyzed based on the shapes of the revetment blocks. The results indicate that for irregularly sized and spaced revetment blocks, such as the natural stone-type vegetation block (Block A), when connected to the revetment in an irregular manner, the changes in flow velocity in the revetment installation zone are more significant than those for Blocks B and C. It is anticipated that considering the topographical characteristics of rivers in the future will enable the design of revetment blocks with practical applicability in the field.

• Knowledge Management Research
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• v.25 no.1
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• pp.135-154
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• 2024

As the digital transformation accelerates, the demand for professionals with competencies in various digital technologies such as artificial intelligence, big data is increasing in the industry. In response, the government is developing various educational programs to nurture talent in these emerging technology fields. However, the lack of a clear definition of competencies, which is the foundation of curriculum development and operation, has posed challenges in effectively designing digital technology education programs. This study systematically reviews the definitions and characteristics of competencies presented in prior research based on a literature review. Subsequently, in-depth interviews were conducted with 30 experts in emerging technology fields to derive a definition of competencies suitable for technology education programs. This research defines competencies for the development of technology education programs as 'a set of one or more knowledge and skills required to perform effectively at the expected level of a given task.' Additionally, the study identifies the elements of competencies, including knowledge and skills, as well as the principles of competency construction. The definition and characteristics of competencies provided in this study can be utilized to create more systematic and effective educational programs in emerging technology fields and bridge the gap between education and industry practice.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.173-189
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• 2023

As supreme technologies continue to be developed, industries such as artificial intelligence, biotechnology, robots, aerospace, electric vehicles, and solar energy are created, and the macro business environment is rapidly changing. Due to these large-scale changes and increased complexity, it is necessary to pay attention to the effect of social capital, which can create new value by utilizing capital increasing the importance of relationships rather than technology or asset ownership itself at the level of start-up strategy. Social capital is a concept first proposed by Hanifan in 1916, and refers to the overall sum of capabilities or resources that are latent or available for use in mutual, continuous, organic relationships or accumulated human relationship networks between individuals or social members. In addition, the diversity of start-up teams with diverse backgrounds, characteristics, and capabilities, rather than one exceptional founder, has been emphasized. Founding team diversity refers to the diversity of in-depth factors such as demographic factors, beliefs, and values of the founding team. In addition, changes in the macro environment are emphasizing the importance of technology start-ups and laboratory start-ups that lead industrial innovation and create the nation's core growth engines. This study focused on the I-Corps' program. I-Corps, which means innovation corps, is a laboratory startup program launched by the National Research Foundation (NSF) in 2011 to encourage entrepreneurship and commercialization of research results. It focuses on forming a startup team involving professors, researchers and market discovery activities. Taking these characteristics into account, this study empirically verified the impact of social capital from a network perspective and founding team diversity on I-Corps start-up performance. As a result of the analysis, the educational diversity of the founding team had a negative (-) effect on the financial performance of the founding team. On the other side, the gender diversity and the cognitive dimension of social capital had a positive (+) effect on the financial performance of the founding team. This study is expected to provide more useful theoretical and practical implications regarding the diversity, social capital, and performance interpretation of the I-Corps Lab startup team.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.144-159
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• 2014

Techniques for making a single panoramic image using multiple pictures are widely studied in many areas such as computer vision, computer graphics, etc. The panorama image can be applied to various fields like virtual reality, robot vision areas which require wide-angled shots as an useful way to overcome the limitations such as picture-angle, resolutions, and internal informations of an image taken from a single camera. It is so much meaningful in a point that a panoramic image usually provides better immersion feeling than a plain image. Although there are many ways to build a panoramic image, most of them are using the way of extracting feature points and matching points of each images for making a single panoramic image. In addition, those methods use the RANSAC(RANdom SAmple Consensus) algorithm with matching points and the Homography matrix to transform the image. The SURF(Speeded Up Robust Features) algorithm which is used in this paper to extract featuring points uses an image's black and white informations and local spatial informations. The SURF is widely being used since it is very much robust at detecting image's size, view-point changes, and additionally, faster than the SIFT(Scale Invariant Features Transform) algorithm. The SURF has a shortcoming of making an error which results in decreasing the RANSAC algorithm's performance speed when extracting image's feature points. As a result, this may increase the CPU usage occupation rate. The error of detecting matching points may role as a critical reason for disqualifying panoramic image's accuracy and lucidity. In this paper, in order to minimize errors of extracting matching points, we used $3{\times}3$ region's RGB pixel values around the matching points' coordinates to perform intermediate filtering process for removing wrong matching points. We have also presented analysis and evaluation results relating to enhanced working speed for producing a panorama image, CPU usage rate, extracted matching points' decreasing rate and accuracy.

• Journal of Korea Technology Innovation Society
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• v.10 no.4
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• pp.654-686
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• 2007

To estimate and analyze an interested science and technology level in any case requires three basic informations: (1) relative positions of our technology level, (2) other relevant technology level of the world best country holding the state of the art technology, and (3) its theoretical or practical maximum level within a certain period of time. Further, additional information from analyzing its respective rate of technology changes is necessary. It seems that most previous empirical or case studies on technology level have not considered third and fourth informations seriously, and thus critically have missed important findings from a dynamic point of view on the matter. A dynamic approach considering types of development processes and paths as well as current position needs an application of a concept of technology development stages and respective growth curves. This paper proposes a new method of approach and application by implementing relatively simple types of the growth curve(S-curve) such as logistic and Comports curves and applying estimation results of these curves to ten core technologies of the growth engines for the next future generation in Korea. The study implies that Korean science and technology level in general clearly gets higher as it approaches to a recent time of period, but relative technology gap from the world best in terms of catching-up period does not get better or narrower in case of at least part of the concerned technologies such as bio new drugs and human organs, and intelligence robots. The possibility does exist that some of our concerned technologies shooting for the next future generation may not come to the world highest level in the near future. The purpose of this study is to propose possibilities of catching-up, if any, by estimating its relevant type of growth pattern by way of measuring and analyzing technology level and by analyzing the technology development process through a position analysis. At this stage this study tries to introduce a new theoretical approach of estimating technology level and its application to existing case study results(data) from Korea Institute of Science and Technology Planning and Evaluation(KISTEP) and Korea Institute of Industrial Technology Evaluation and Planing(ITEP), for years of 2004 and 2006 respectively. The study has some limitations in terms of accuracy of measuring(estimating) a relevant growth curve to a particular technology, feasibility of applying estimated results, accessing and analyzing panel experts opinions. Hence, it is recommended that further study would follow soon enough to verify practical applicability and possible expansion of the study results.

• Journal of Korean Home Economics Education Association
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• v.31 no.4
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• pp.149-161
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• 2019

At present, we are at the point of change of the 4th industrial revolution era due to the development of artificial intelligence(AI) and rapid technological innovation that no one can predict until now. This study started from the question of 'What role should home economics education play in the era of the Fourth Industrial Revolution?'. The Fourth Industrial Revolution is characterized by AI, cloud computing, Internet of Things(IoT), big data, and Online to Offline(O2O). It will drastically change the social system, science and technology and the structure of the profession. Since the dehumanization of robots and artificial intelligence may occur, the 4th Industrial Revolution Education should be sought to foster future human resources with humanity and citizenship for the future community. In addition, the implication of education in the fourth industrial revolution, which will bring about a change to a super-intelligent and hyper-connected society, is that the role of education should be emphasized so that humans internalize their values as human beings. Character education should be established as a generalized and internalized consciousness with a concept established in the integration of the curriculum, and concrete practical strategies should be prepared. In conclusion, home economics education in the 4th industrial revolution era should play a leading role in the central role of character education, and intrinsic improvement of various human lives. The fourth industrial revolution will change not only what we do, or human mental and physical activities, but also who we are, or human identity. In the information society and digital society, it is important how quickly and accurately it is possible to acquire scattered knowledge. In the information society, it is required to learn how to use knowledge for human beings in rapid change. As such, the fourth industrial revolution seeks to lead the family, organization, and community positively by influencing the systems that shape our lives. Home economics education should take the lead in this role.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Cross-Cultural Studies
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• v.50
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• pp.31-51
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• 2018

The concept of 'monsters' have become popular, again, in recent times. A number of 'monster narratives' that discuss monsters such as zombies, humanoids, viruses, extraterrestrials, and serial killers have been made and re-made in popular media. Noting such an interesting cultural context, this article attempts, first, to find out some essential prototypical elements of a monster narrative and, second, to relate it with a catastrophic narrative. Correspondingly, the word 'monster' has been used as a conceptual prototype category that denies universal and clear definition, which makes it as one of the most widely used and familiar subjects of the use of metaphor. The prototypical meanings of various monster figures can be converged on a certain creature of being in this way held out as bizarre, curious, and abnormal. The monster figure that surpasses existing normality is also connected to 'abjection,' such as something that is cast aside from the body such as the bodily functions seen in its associated blood, tears, vomit, excrement, or semen, and so on. Nevertheless, both the monster figure and abjection produce disgust and horror in the minds of ordinary spectators or readers of media using this metaphor to heighten excitement for the viewers. The abject characteristic of the monster figure also has something in common with the posthuman figure, meaning to apply to a category of inhuman others who are held outside of the normal category of human beings. In the similar vein, it is natural that the most typical monster figures in our times are posthuman creatures embodied in such forms as seen with zombies, humanoids, cyborgs, robots, and so on. In short, the monster figure includes all of the creatures and beings that disarray normalized humanist categories and values. The monster narrative, in the same sense, is a type of story that tells about others outside modern, anthropocentric, male-centered, and Westernized categories of thought. It can be argued that a catastrophic narrative, a literary genre which depicts the world where a series of catastrophic events demolish the existing human civilization, ought to be seen as a typical modern-day monster narrative, because it also discounts and criticizes normalized humanist categories and values as is the result of the monster narrative. Going beyond the prevailing humanist realist narrative that are so familiar with existing values, the catastrophic narrative is not only a monster narrative per se, but also a monstrous narrative which disrupts and reinvents currently mainstream narratives and ways of thinking.