• International Journal of High-Rise Buildings
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• v.9 no.1
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• pp.105-111
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• 2020

In recent years the construction sector has grown significantly in terms of investment and research on robotics and automation, yet it is still a low-tech and disjointed industry. One of the main scopes of this paper is to determine how robotic automation can provide the answers to the needs this industry has. To that end, an overall framework and development agenda of current technological innovation in the field has been outlined. Possible drawbacks and driving forces in the development of robots in the construction site have been identified. In addition, the review provides for state-of-the-art policies and regulations, as well as the short and medium-term outlook in different markets and countries. Ultimately, the forecast impact on traditional processes, construction sites, emerging technologies and related professions has been summarized in order to delineate prospective repercussions and future directions towards self-sufficiency.

• Annual Conference of KIPS
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• 2022.11a
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• pp.746-748
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• 2022

투자 분배 시스템은 지속성, 수익성, 변동성, 하방경직성 등 각각의 지표를 찾아내는 데이터 분석을 조합한 시스템으로 MLP 신경망을 통한 시황을 예측으로 투자 경험이 부족한 일반 사용자에게 안정적인 투자 분배 전략을 제공한다. 투자분배 시스템 구현을 위하여 추가적으로 금융시장에 대한 회귀분석, 켈리 공식과 같은 도구를 활용하였다.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.247-254
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• 2020

The socio-cultural and economic changes following the Fourth Revolution are driving the growth of the food tech industry. Korea's food tech industry is still focused on delivery apps and the smart farms, robot market including artificial intelligence are in its infancy. In the United States, alternative meat companies are already included in unicorn companies, while Korea, the fourth largest importer of beef, lacks alternative meat development. France, Europe's largest agricultural country, is focusing on Agtech. China has developed the Internet and online e-commerce market with the world's number one population. Korea also needs to change regulations that focus on the past industry and various food tech industries should be developed through political and business-driven research and investment.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.181-186
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• 2002

Laser welding application for car body manufacturing has many advantages in the stiffness and the lightness of vehicle, the productivity of assembly line, and the degree of freedom in design. This presentation will express the innovation of car body manufacturing including parameter optimization, process modeling, and system integration. In this application the investment for systems was cut down dramatically by real time switching over the laser path between two welding stations. Points of technical discussion are as follows: optimization of parameters such as laser power, robot speed and trajectory, compact and useful design of jig & fixture to assure welding quality for 3 sheet-layer zinc-coated steel, system integration between 4kW Nd:YAG laser device and the other systems, on-line real time welding quality monitoring system, perfect safety standards for high power laser, minimization of consumption costs such as arc lamp, protective glass for optic, etc. Laser welding has found a place on Hyundai's production plant in conjunction with the startup of mass production of new sports car, and this production system is the result of a collaboration of its engineers. Outer side sheets are joined to inner side sheets by 122 stitch welds totally. And the length is about 2.4meter.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.142-159
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• 1996

Engineering of automated tools for the agro-food industries and the rural world activities have to pick up two challenges : to answer the immediate important problems related to the situation of these industries, and to imaging the tools that their professional will need next century. Creating or modifying automated tools in the next few will be made taking into account parameters either technical (environmental protection, health and safety), or social and economical (investment , employment). There will be a strong interaction with disciplines like ecology, medicine, ergonomy, psycho-sociology , etc. , The partners for such a research, tools manufactures and users, should have an early involvement in its content, in order to find rapidly the solution to the drastic problems they are meeting. On a longer term , during the next 20 years , there will be an important evolution of the rural space management and of the food processes. This will imply the emergence of new types of activities and know-how's , with lines of automated tools to be invented and developed , like : micro-system for organic localized tasks -mobile and adaptive equipments highly autonomous for natural space actions - device for perception , decision and control reproducing automatically the expert behaviors of human operators. Design of such automated tools need to overcome technological difficulties like the automation of the expert-decision process, or the management of complex design.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.3
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• pp.274-290
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• 2019

This article links the change in regional manufacturing employment in Korea after the financial crisis to the geography of technological and trade shocks. We conceptualize the trade shock as the rapid growth in Korean imports from and exports to China and ASEAN countries. We then measure the exposure to technological shocks as the degree to which regions are specialized in routine tasks, which are susceptible to automation technologies. Results show that local labor markets specialized in routine tasks experience significant falls in manufacturing employment. Regions whose industrial structure exposes them to rising import competition experience sharp drop in manufacturing employment. We also found that export plays a major role in explaining the growth of regional manufacturing employment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.611-616
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• 2018

With the recent increase in awareness of the diversification of patterns of warfare and security, technological evolution is occurring in the field of autonomous defense robots. As defense science and technology develops with the development of the concept of military utilization focusing on human lives and economic operation, the importance of autonomous robots in the effect-oriented future battlefield is increasing. The major developed countries have developed core technologies, investment strategies, priorities, data securing strategies and infrastructure development related to the field of autonomous defense robots, and research activities such as technology planning and policy strategy for autonomous defense robots in Korea have already begun. In addition, the field of autonomous defense robots encompasses technologies that represent the fourth industrial revolution, such as artificial intelligence, big data, and virtual reality, and so the expectations for this future area of technology are very high. It is difficult to predict the path of technological development due to the increase in the demand for new rather than existing technology. Moreover, the selection and concentration of strategic R&D is required due to resource constraints. It is thought that a preemptive response is needed. This study attempts to derive 6 new technologies that will shape the future of autonomous defense robots and to obtain meaningful results through an empirical study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.612-618
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• 2020

In recent years, the demand for external window cleaning has increased, but the process is a very dangerous manpower-dependent operation. In addition, it is difficult to clean at the desired frequency in a business that values cleanliness. Therefore, there is a need to automate this work. This paper presents the concept of a device that can be attached to a specific window and clean the window continuously. The economic feasibility of this device was analyzed. The estimated manufacturing cost of the equipment was approximately 10 million won, but the possible investment cost was at least 9.8 million won for five years of endurance and 103 million won for 10 years of endurance. Therefore, the expected savings well exceed the equipment cost, and it was evaluated as having economic feasibility. Since this study analyzed only quantitative indicators, the expected cost reduction due to a reduction in safety accidents, productivity improvement, construction time reduction, and quality improvement was not considered. Therefore, it is expected that the calculated economic feasibility will be more accurate if the cost reduction effect by the automation equipment is calculated by adding the expected values not considered in this study.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.187-194
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• 2022

This study is to encourage physical activity and exercise in people with spinal cord disabilities so that they can have a positive effect on health outcomes. Current evidence shows that IT-based muscle strength and muscle endurance, cardiopulmonary exercise, electrical stimulation exercise, and robot exercise can all improve physical components, reduce the risk of secondary health complications, and have a positive impact on the overall health of people with chronic physical disabilities. To improve muscle strength and muscle endurance, exercise frequency should be conducted twice and three sets a week, <5 Reps to improve muscle strength, general strength should be repeated 6 to 15 times, and 15 to 30 times to improve muscle endurance. In order to improve cardiopulmonary ability, it should be conducted 3-5 times a week, 20-60 minutes, and 50-80% of the maximum heart rate. Therefore, higher resource investment is needed to realize various IT-based exercise benefits and access professional equipment, facilities and trainers.

• 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.