• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.995-1002
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• 2006

Construction equipment plays an important role as one of resources in construction process. It is obvious that the machine intensive construction method achieves productivity and quality improvement as well as safety improvement. The number of registered construction equipment in Korea is over 320,000 in 2005 according to the national statistics safety, but recent crisis of construction equipment industrialist has been deepen by lack of skilled workers, rise in wages, diminution of working and etc. The main objective of this paper is to propose an improved management and application policy for the better construction equipment utilization. A classification method for construction equipment and a licensing system for construction equipment operators are newly suggested to revise the Construction Equipment Management Law. In order to satisfy the objective, this research performs literature reviews on domestic and overseas related laws and regulations for operating license, and conducts surveys and interviews with experts in the field of construction equipment industry. The results of this research can be considered as an important reference to update the Law that can improve construction productivity and equipment operating rate.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.37-44
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• 2023

As a primary technology of Industry 4.0, human-robot collaboration (HRC) requires additional measures to ensure worker safety. Previous studies on avoiding collisions between collaborative robots and workers mainly detect collisions based on sensors and cameras attached to the robot. This method requires complex algorithms to continuously track robots, people, and objects and has the disadvantage of not being able to respond quickly to changes in the work environment. The present study was conducted to implement a web-based platform that manages collaborative robots by recognizing the emotions of workers - specifically their perception of danger - in the collaborative process. To this end, we developed a web-based application that collects and stores emotion-related brain waves via a wearable device; a deep-learning model that extracts and classifies the characteristics of neutral, positive, and negative emotions; and an Internet-of-things (IoT) interface program that controls motor operation according to classified emotions. We conducted a comparative analysis of our system's performance using a public open dataset and a dataset collected through actual measurement, achieving validation accuracies of 96.8% and 70.7%, respectively.

• Industry Promotion Research
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• v.8 no.4
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• pp.251-256
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• 2023

The purpose of this study is to find out how much research has been done on dream analysis based on S.Freud's psychoanalytic theory, and to suggest the necessity of dream research and follow-up research on dream research. The research method was based on analysis of domestic academic journals from 2019 to 2023, a study on S.Freud's dream analysis. Among them, the data were collected and organized through a keyword classification process from the Research Information Service (RISS) and the Korean Journal Citation Index (KCI). The classification categories were psychoanalysis, domestic academic journals, dream analysis, dream interpretation, dream analysis research trends, and dream research trends. In particular, psychoanalysis, dream analysis, domestic academic journals, and research trends were searched. The conclusion was drawn as follows. First, studies on research trends on dream analysis in domestic academic journals did not occupy a large proportion. Second, the ratio of research trends centered on dream analysis keywords was also significantly low. Third, the use and frequency of dream analysis was low. Fourth, research on Korean testing tools based on dream analysis is needed.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.21-30
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• 2024

This research aims to design a system capable of generating real web pages based on deep learning and big data, in three stages. First, a classification system was established based on the industry type and functionality of e-commerce websites. Second, the types of components of web pages were systematically categorized. Third, the entire web page auto-generation system, applicable for deep learning, was designed. By re-engineering the deep learning model, which was trained with actual industrial data, to analyze and automatically generate existing websites, a directly usable solution for the field was proposed. This research is expected to contribute technically and policy-wise to the field of generative AI-based complete website creation and industrial sectors.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.227-231
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• 2024

This study purports to examine the potential effects of welfare attitudes of Korean people upon their political orientation. The 17^th Korea Welfare Panel Data(KWPD) in 2022 are used for this purpose. Independent variable include sex, age, education, interest in politics, and employment status. Discriminant analysis show several results. First and foremost, pre-established discriminant function works well for classification of respondents' liberal vs conservative stance. Secondly, except gender and dummy variable for temporary employed, all independent variables contribute significantly for the classification at a given significance level. . Finally, welfare attitudes of respondents', measured by universalism vs selectivism and the attitudes upon increasing tax for welfare expenditures are found to be significant and relatively big impacts upon dependent variable, compard to other variables in the model. The nature of causal relationship between welfare attitudes and political orientation remains for further study.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.139-160
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• 2017

Technology commercialization creates effective economic value by linking the company's R & D processes and outputs to the market. This technology commercialization is important in that a company can retain and maintain a sustained competitive advantage. In order for a specific technology to be commercialized, it goes through the stage of technical planning, technology research and development, and commercialization. This process involves a lot of time and money. Therefore, the duration and cost of technology commercialization are important decision information for determining the market entry strategy. In addition, it is more important information for a technology investor to rationally evaluate the technology value. In this way, it is very important to scientifically estimate the duration and cost of the technology commercialization. However, research on technology commercialization is insufficient and related methodology are lacking. In this study, we propose an evaluation model that can estimate the duration and cost of R & D technology commercialization for small and medium-sized enterprises. To accomplish this, this study collected the public data of the National Science & Technology Information Service (NTIS) and the survey data provided by the Small and Medium Business Administration. Also this study will develop the estimation model of commercialization duration and cost of R&D performance on using these data based on the market approach, one of the technology valuation methods. Specifically, this study defined the process of commercialization as consisting of development planning, development progress, and commercialization. We collected the data from the NTIS database and the survey of SMEs technical statistics of the Small and Medium Business Administration. We derived the key variables such as stage-wise R&D costs and duration, the factors of the technology itself, the factors of the technology development, and the environmental factors. At first, given data, we estimates the costs and duration in each technology readiness level (basic research, applied research, development research, prototype production, commercialization), for each industry classification. Then, we developed and verified the research model of each industry classification. The results of this study can be summarized as follows. Firstly, it is reflected in the technology valuation model and can be used to estimate the objective economic value of technology. The duration and the cost from the technology development stage to the commercialization stage is a critical factor that has a great influence on the amount of money to discount the future sales from the technology. The results of this study can contribute to more reliable technology valuation because it estimates the commercialization duration and cost scientifically based on past data. Secondly, we have verified models of various fields such as statistical model and data mining model. The statistical model helps us to find the important factors to estimate the duration and cost of technology Commercialization, and the data mining model gives us the rules or algorithms to be applied to an advanced technology valuation system. Finally, this study reaffirms the importance of commercialization costs and durations, which has not been actively studied in previous studies. The results confirm the significant factors to affect the commercialization costs and duration, furthermore the factors are different depending on industry classification. Practically, the results of this study can be reflected in the technology valuation system, which can be provided by national research institutes and R & D staff to provide sophisticated technology valuation. The relevant logic or algorithm of the research result can be implemented independently so that it can be directly reflected in the system, so researchers can use it practically immediately. In conclusion, the results of this study can be a great contribution not only to the theoretical contributions but also to the practical ones.

• Proceedings of the Korean Environmental Health Society Conference
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• 2005.06a
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• pp.240-248
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• 2005

To implement a globally harmonized system of classification and labeling of chemicals (GHS) in Korea, an interminsterial GHS working group involving 6 ministries established an expert working group composed of 7 experts from relevant organizations and one private consultant to prepare an officialKorean GHS version by March, 2005. As such, the translation and review of the official Korean GHS version, including annexes, started in October, 2004 and was completed on March 15, 2005. The official Korean GHS version has now been posted on the websites of the relevant ministries and organizations to solicit public opinions. The official Korean GHS version will be finalized after a public hearing scheduled forMay, 2005. Collaborative efforts as regards implementing and disseminating the GHS in Korea will be continued to avoid any confusion or duplication and for effective use of resources. The globally harmonized system of classifying and labeling chemicals (GHS) was originally adopted in 1992 at the United Nations Conference on Environment and Development (UNCED), as subsequently reflected in Agenda 21 chapter 19. The work was coordinated and managed under the auspices of the Interorganization Programme for the Sound Management of Chemicals(IOMC) Coordinating Group for the Harmonization of Chemical Classification Systems (UNCEGHS). The technical focal points for completing the work were the International Labour Organization (ILO); Organization for Economic Cooperation and Development (OECD); and United Nations Economic and Social Council's Subcommittee of Experts on the Transport of Dangerous Goods (UNSCETDG). The work was finalized in October 2002, and the World Summit on Sustainable Development in Johannesburg on 4 September 2002 encouraged countries to implement the new GHS as soon as possible with a view to having the system fully operational by 2008 (UN, 2003). Implementation has already started with pilot countries introducing the system to their national practices in different regions of the world. The GHS text, called the purple book, becameavailable as a W publication in early 2003. The GHS text, called the purple book, becameavailable as a UN publication in early 2003. The GHS system will be kept dynamic, and regularly revised and made more efficient as experience is gained in its implementation. While national or regional governments are the primary audiences for this document, it also contains sufficient context and guidance for those in industry who will ultimately be implementing the national requirements that will be introduced (UN, 2003). The Japanese government published their official Japanese GHS version, the first in Asia, in April 2004 after starting work in January 2003 based on an interministerial chemical coordination committee involving 7 ministries, including the Ministry of Foreign Affairs, Ministry of Internal Affairs and Communications, Ministry of Health, Labour, and Welfare, Ministry of Agriculture, Forestry and Fisheries, Ministry of Economy, Trade and Industry, Ministry of Land, Infrastructure, and Transport, and Ministry of Environment (MOE, 2004). Accordingly, similar to the Japanese GHS efforts, this paper presents the interministerial efforts involved in publishing the official Korean GHS version.

• Analytical Science and Technology
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• v.24 no.5
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• pp.387-394
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• 2011

This study was performed to investigate the contents and leaching characteristics of hazardous wastes from the paint industry. In order to establish a hazardous waste list, samples from industrial discharge have been analyzed for 8 non-regulated inorganic hazardous substances (i.e., Sb, Ni, F, V, Ba, Zn, Be, Se). In more detail, hazardous waste samples from a total of 64 workplaces, e.g. manufacture, formulation, supply and use (MFSU) of coatings, adhesives, sealants and printing inks processing, have been chosen and analyzed. Contents and leaching tests for inorganic metal species in samples show that the non-regulated hazardous substances satisfy all the criteria, while quantitative analyses reveal that some samples of the discharged wastes exceeded the criteria proposed by NIER (National Instituted of Environmental Research). In conclusion, we expect the outcome of this study to align the classification system of hazardous waste management in South Korea with international legislations, and consequently contribute to reduce environmental pollution as well as health risks by toxic wastes.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.167-172
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• 2006

It follows recently in an order augmentation of overseas construction market plant field and the project of oil gas field is increasing. Consequently, the hazard which secures the competitive power of the overseas plant enterprise of the domestic building industry enterprises the technical competitiveness security which stands, productivity improvement and strategy management propulsion back positive disposal plan establishment are demanded. Even from in that oil gas field of overseas plant enterprise for an industrial competitive power improvement the application of EPC circulation information which relates with a project accomplishment is more demanded, the EPC phased star efficiently it manages the circulation information contents which occurs from the business which is various it is not presented it cannot there is a contents classification system for. If with him about lower the draft the problem point of information omission back of occurrence and business subject for of the fringe land and duplication business occurs, about lower the productivity decrease actual condition is appearing with such problem point. The research which it sees consequently in order to improve the use characteristic of the augmentation of practical application of the contents management system of oil gas field and building industry information civil official establishhes the contents management system the BPM for (Business Process Management) to present the contents classification system of base, it does to sleep. The part of Business Process materiality the knowledge which is demanded, contents information and system anger it analyzes system anger of industrial equipment circulation information it takes a triangular position and to sleep it does.