• Analyses & Alternatives
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• v.2 no.1
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• pp.31-69
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• 2018

This study examines the role of science in resolving trade disputes. After the Great East Japan Earthquake of 11 March 2011 that not only jeopardized the people of Japan, but also put the safety of an entire region at risk, the Republic of Korea (Korea) has imposed import bans as well as increased testing and certification requirements for radioactive material on Japanese food products. Japan has challenged these restrictions at the World Trade Organizations Dispute Settlement Body (DSB). This study aims to explain how international trade agreements and previous DSB rulings have dealt with different scientific viewpoints provided by confronting parties. In doing so, it will contrast the viewpoints espoused by Korean and Japanese representatives, and then analyzes the most similar case studies previously ruled on by the DSB, including the case of beef hormones and the case of genetically modified crops including biotech corn, both between the United States and the European Communities (EC). This study finds that science is largely subordinate to national interests in the case of state decision-making within the dispute settlement processes, and science has largely been relegated to a supportive role. Due to the ambiguity and lack of truly decisive decisions in the Appellate Body in science-based trade disputes, this study concludes that the Appellate Body avoids taking a firm scientific position in cases where science is still inconclusive in any capacity. Due to the panel's unwillingness to establish expert review boards as it has the power to do, instead favoring an individual-based system so that all viewpoints can be heard, it has also developed a system with its own unique weaknesses. Similar to any court of law in which each opposing party defends its own interests, each side brings whatever scientific evidence it can to defend its position, incentivizing them to disregard scientific conclusions unfavorable to their position. With so many questions that can arise, combined with the problems of evolving science, questions of risk, and social concerns in democratic society, it is no wonder that the panel views scientific information provided by the experts as secondary to the legal and procedural issues. Despite being ruled against the EC on legal issues in two previous cases, the EC essentially won both times because the panel did not address whether its science was correct or not. This failure to conclusively resolve a debate over whose science is more scientific enabled the EC to simply fix the procedural issues, while continuing to enforce trade restrictions based on their scientific evidence. Based on the analysis of the two cases of disputes, Korea may also find itself guilty of imposing an unwarranted moratorium on Japan's fish exports, only to subsequently pass new restrictions on labelling and certification requirements because Japan may have much scientific evidence at its disposal. However, Korea might be able to create enough uncertainty in the panel to force them to rule exclusively on the legal issues of the case. This will then equip Korea, like the EC in the past, with a way of working around the ruling, by changing whatever legal procedure they need to while maintaining some, if not most, of its restrictions when the panel fails to address its case on scientific grounds.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1249-1249
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• 2022

The facade, an exterior material of a building, is one of the crucial factors that determine its morphological identity and its functional levels, such as energy performance, earthquake and fire resistance. However, regardless of the type of exterior materials, huge property and human casualties are continuing due to frequent exterior materials dropout accidents. The quality of the building envelope depends on the detailed design and is closely related to the back frames that support the exterior material. Detailed design means the creation of a shop drawing, which is the stage of developing the basic design to a level where construction is possible by specifying the exact necessary details. However, due to chronic problems in the construction industry, such as reducing working hours and the lack of design personnel, detailed design is not being appropriately implemented. Considering these characteristics, it is necessary to develop the detailed design process of exterior materials and works based on the domain-expert knowledge of the construction industry using artificial intelligence (AI). Therefore, this study aims to establish a detailed design automation algorithm for AI-based condition-responsive exterior wall panels and their back frames. The scope of the study is limited to "detailed design" performed based on the working drawings during the exterior work process and "stone panels" among exterior materials. First, working-level data on stone works is collected to analyze the existing detailed design process. After that, design parameters are derived by analyzing factors that affect the design of the building's exterior wall and back frames, such as structure, floor height, wind load, lift limit, and transportation elements. The relational expression between the derived parameters is derived, and it is algorithmized to implement a rule-based AI design. These algorithms can be applied to detailed designs based on 3D BIM to automatically calculate quantity and unit price. The next goal is to derive the iterative elements that occur in the process and implement a robotic process automation (RPA)-based system to link the entire "Detailed design-Quality calculation-Order process." This study is significant because it expands the design automation research, which has been rather limited to basic and implemented design, to the detailed design area at the beginning of the construction execution and increases the productivity by using AI. In addition, it can help fundamentally improve the working environment of the construction industry through the development of direct and applicable technologies to practice.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.3
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• pp.43-54
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• 1997

Knowledge acquisition is one of the most difficult problems in designing fuzzy systems. As application domains of fuzzy systems become larger and more complex, it is more difficult to find the relations among the system's input- outpiit variables. Moreover, it takes a lot of efforts to formulate expert's knowledge about complex systems' control actions by linguistic variables. Another difficulty is to define and adjust membership functions properly. Soin conventional fuzzy systems, the membership functions should be adjusted to improve the system performance. This is time-consuming process. In this paper, we suggest a new approach to design a fuzzy system. We design a fuzzy system using two neural networks, Kohonen neural network and backpropagation neural network, which generate fuzzy rules automatically and construct inference network. Since fuzzy inference is performed based on fuzzy relation in this approach, we don't need the membership functions of each variable. Therefore it is unnecessary to define and adjust membership functions and we can get fuzzy rules automatically. The design process of fuzzy system becomes simple. The proposed approach is applied to a simulated automatic car speed control system. We can be sure that this approach not only makes the design process of fuzzy systems simple but also produces appropriate inference results.

• The Korean Society of Law and Medicine
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• v.22 no.4
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• pp.117-157
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• 2021

This research reviewed the HIPAA/HITECH, 21st Century Cures Act, Common Law, and private Guidances from the perspectives in protecting and utilitizing the medical data, while implications were followed. First, the standards for protection and utilization are relatively clearly regulated through single law on personal medical information in the United States. The HIPAA has been introduced in 1996 as fundamental act on protection of medical data. Medical data was divided into personally identifiable information, non-identifying information, and limited dataset under HIPAA. Regulations on de-identification measures for medical information, objects for deletion of limited data sets, and agreement on prohibition of data re-identification were stipulated. Moreover, in the 21st Century Cures Act regulated mutual compatibility for data sharing, prohibition of data blocking, and strengthening of accessibility of data subjects. Common Law introduced comprehensive consent system and clearly stipulates procedures. Second, the regulatory system is relatively simplified and clearly stipulated in the United States. To be specific, the expert consensus and the safe harbor system were introduced as an anonymity measure for identifiable medical information, which clearly defines the process while increasing trust. Third, the protection of the rights of the data subject is specified, the duty of explanation is specified in detail, while the information right of the consumer (opt-out procedure) for identification information is specified. For instance, the HHS rule and FDA regulations recognize the comprehensive consent system for human research, but the consent procedure, method, and requirements are stipulated through the common rule. Fourth, in the case of the United States, a trust-based system is being used throughout the health and medical data legislation. To be specific, Limited Data Sets are allowed to use in condition to the researcher's agreement to prohibit re-identification, and de-identification or consent process is simplified under the system.

• Journal of Information Management
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• v.39 no.3
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• pp.95-113
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• 2008

In todays environment in which scientific technologies are changing very fast than ever, companies have to monitor and search emerging technologies to gain competitiveness. Actually many nations try to do that. Most of them use Dephi approach based on experts review as a searching method. But experts review has been criticised for probability of inclination and its derivative problems in the sense that it is accomplished only by expert's subjectivity. To overcome such problems, we used Scientometric Method for identifying emerging technology that had been done by Delphi as a rule. We made three particular efforts in order to improve the Quality of the result. Firstly, we selected one alternative database between SCI and Scopus hoping to see evenly-distributing results in wide fields on the front burner. Secondly we used Fractional citation counting in counting citation number in the stage of linear regression analysis. Lastly, we verified Scientometric result with experts opinions to minimize probable errors in a Scientometric research. As a result, we derived 290 emerging technologies from Scientometric analysis with Scopus Database, and visualized them on 2-dimension map with data mining system named KnowledgeMatrix which was developed by KISTI.