• Journal of Nuclear Fuel Cycle and Waste Technology
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• v.1 no.1
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• pp.9-27
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• 2013

Nagra was established in 1972 by the Swiss nuclear power plant operators and the Federal Government to implement permanent and safe disposal of all types of radioactive waste generated in Switzerland. The Swiss Nuclear Energy Act specifies that these shall be disposed of in deep geological repositories. A number of different geological formations and sites have been investigated to date and an extended database of geological characteristics as well as data and state-of-the-art methodologies required for the evaluation of the long-term safety of repository systems have been developed. The research, development, and demonstration activities are further supported by the two underground research facilities operating in Switzerland, the Grimsel Test Site and the Mont Terri Project, along with very active collaboration of Nagra with national and international partners. A new site selection process was approved by the Federal Government in 2008 and is ongoing. This process is driven by the long-term safety and feasibility of the geological repositories and is based on a step-wise decision-making approach with a strong participatory component from the affected communities and regions. In this paper a brief history and the current status of the Swiss radioactive waste management program are presented and special characteristics that may be useful beyond the Swiss program are highlighted and discussed.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1145-1152
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• 2024

Digital transformation has become a pivotal focus in the Architecture, Engineering, and Construction (AEC) industry, driven by an urgent need to enhance productivity and optimize resource management. This transformation plays an essential role throughout the entire project lifecycle, from the early stages of conception to the final phases of completion. The paper underscores the critical importance of aligning digital transformation initiatives with the broader business strategies of AEC organizations. This alignment is key to gaining a competitive edge and fostering sustainable growth within the industry. The paper introduces a comprehensive and adaptable strategic framework for digital transformation. This framework is designed to be flexible, allowing AEC organizations to tailor digital transformation strategies to meet their specific needs and objectives. The framework not only addresses the technological aspects but also considers the cultural and operational shifts required for successful implementation. Moreover, the paper delves into various aspects of digital transformation, such as data management, workflow automation, and the integration of emerging technologies like AI and IoT in AEC processes. It discusses the potential barriers to digital adoption and offers strategies to overcome these challenges. This paper serves as an in-depth guide for AEC organizations looking to seamlessly integrate digital technologies into their business models. It provides valuable insights and methodologies that are crucial for any entity in the AEC industry striving to thrive in an increasingly digitalized world, making it a must-read for leaders and decision-makers within the industry.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.47-53
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• 2021

With increasing interest in the 4th industrial revolution, data-driven scientific methodologies have developed. However, there are limitations of data collection in the real estate field of research. In addition, as the public becomes more knowledgeable about the real estate market, the qualitative sentiment comes to play a bigger role in the real estate market. Therefore, we propose a method to collect quantitative data that reflects sentiment using text mining and k-means algorithms, rather than the existing source data, and to predict the direction of housing index through artificial neural network learning based on the collected data. Data from 2012 to 2019 is set as the training period and 2020 as the prediction period. It is expected that this study will contribute to the utilization of scientific methods such as artificial neural networks rather than the use of the classical methodology for real estate market participants in their decision making process.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.585-594
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• 2024

In recent years, the construction industry has rapidly adopted offsite-manufacturing and distributed construction methods. This change brings a variety of challenges requiring innovative solutions, such as the utilization of AI-driven and generative design. Numerous studies have explored the concept of multi-objective generative design with genetic algorithms in construction. However, this paper highlights the challenges and proposes a solution for combining generative design with distributed construction to address the need for agility in design. To achieve this goal, the research delves into the development of a multi-objective generative design optimization using a weighted genetic algorithm based on simulated annealing. The specific design case adopted is an educational complex. The proposed process strives for scalable economic viability, environmental comfort, and operational efficiency by optimizing modular configurations of architectural spaces, facilitating affordable, scalable, and optimized construction. Rhino-Grasshopper and Galapagos design tools are used to create a virtual environment capable of generating architectural configurations within defined boundaries. Optimization factors include adherence to urban regulations, acoustic comfort, and sunlight exposure. A normalized scoring approach is also presented to prioritize design preferences, enabling systematic and data-driven design decision-making. Building Information Modeling (BIM) tools are also used to transform the optimization results into tangible architectural elements and visualize the outcome. The resulting process contributes both to practice and academia. Practitioners in AEC industry could gain benefit through adopting and adapting its features with the unique characteristics of various construction projects while educators and future researchers can modify and enhance this process based on new requirements.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.173-183
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• 2019

Sejong, Korea's special multifunctional administrative city, was created as a national project to relocated government ministries, the aim being to pursue more balanced regional economic development and boost national competitiveness. During the second phase development will focus on mitigating the challenges raised due to the increasing population and urbanization development. All of infrastructure, apartments, houses, private buildings, commercial structures, public buildings, citizens are producing more and more complex data. To face these challenges, Sejong city governments and policy maker recognizes the opportunity to ensure more enriched lives for citizen with data-driven city management, and effectively exploring how to use existing data to improve policy services and a more sustainable economic policy to enhance sustainable city management. As a city government is a complex decision making system, the analysis of astounding increase in city dada is valuable to gain insight in the affecting traffic flow. To support the requirement specification and management of government policy making, the graphic representation of information and data should be provide a different approach in the intuitive way. With in context, this paper outlines the design of interactive, web-based dashboard which provides data visualization regarding better policy making and risk management.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.30-39
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• 2024

This study introduces a novel approach for identifying potential failure risks in missile manufacturing by leveraging Quality Inspection Management (QIM) data to address the challenges presented by a dataset comprising 666 variables and data imbalances. The utilization of the SMOTE for data augmentation and Lasso Regression for dimensionality reduction, followed by the application of a Random Forest model, results in a 99.40% accuracy rate in classifying missiles with a high likelihood of failure. Such measures enable the preemptive identification of missiles at a heightened risk of failure, thereby mitigating the risk of field failures and enhancing missile life. The integration of Lasso Regression and Random Forest is employed to pinpoint critical variables and test items that significantly impact failure, with a particular emphasis on variables related to performance and connection resistance. Moreover, the research highlights the potential for broadening the scope of data-driven decision-making within quality control systems, including the refinement of maintenance strategies and the adjustment of control limits for essential test items.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.328-342
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• 2022

The Internet of Things (IoT) is a technology that offers lucrative services in various industries to facilitate human communities. Important information on people and their surroundings has been gathered to ensure the availability of these services. This data is vulnerable to cybersecurity since it is sent over the internet and kept in third-party databases. Implementation of data encryption is an integral approach for IoT device designers to protect IoT data. For a variety of reasons, IoT device designers have been unable to discover appropriate encryption to use. The static support provided by research and concerned organizations to assist designers in picking appropriate encryption costs a significant amount of time and effort. IoTES is a web app that uses machine language to address a lack of support from researchers and organizations, as ML has been shown to improve data-driven human decision-making. IoTES still has some weaknesses, which are highlighted in this research. To improve the support, these shortcomings must be addressed. This study proposes the "IoTES with Security" model by adding support for the security level provided by the encryption algorithm to the traditional IoTES model. We evaluated our technique for encryption algorithms with available security levels and compared the accuracy of our model with traditional IoTES. Our model improves IoTES by helping users make security-oriented decisions while choosing the appropriate algorithm for their IoT data.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1313-1313
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• 2024

This paper proposes the development of an advanced Risk Management System (RMS) using Risk-Based Methodologies (RBM) specifically tailored for addressing construction defects in industrial plants. Urbanization and industrialization demand robust frameworks to handle the complexities and safety concerns in construction projects. Traditional risk management often overlooks critical aspects such as persistent construction defects. This paper discusses the development of an innovative Risk Management System (RMS) that integrates Risk-Based Methodologies (RBM) specifically for construction defect mitigation in industrial settings. The study centers around the implementation of Risk-Based Inspection (RBI) techniques, tailored to enhance traditional risk management systems. This includes developing a specialized risk assessment tool alongside an online management platform, designed to provide continuous monitoring and comprehensive management of construction risks. The proposed system-RBE-i (Risk-Based Execution for Installation)-focuses on identifying, evaluating, and mitigating risks effectively, utilizing a systematic approach that integrates seamlessly into existing construction workflows. The RBE-i system's core lies in its ability to conduct thorough risk analyses and real-time data provision. It uses digital technologies to improve communication, operational efficiency, and decision-making processes across construction projects. By applying these methodologies, the system enhances safety and ensures more efficient project execution by preemptively identifying potential risks and addressing them promptly. Field applications of RBE-i have demonstrated its effectiveness in significantly reducing construction defects, thus validating its potential as a transformative tool in construction risk management. The system sets new industry standards by shifting from reactive to proactive risk management practices, ultimately leading to safer, more reliable, and cost-effective construction operations. In conclusion, the RMS developed through this study not only addresses the pressing needs of construction risk management but also proposes a paradigm shift towards more proactive, structured, and technology-driven practices. The successful integration of the RBE-i system across various pilot projects illustrates its significant potential to improve overall project outcomes, making it an invaluable addition to the field of construction management.

• Journal of Science and Technology Studies
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• v.18 no.2
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• pp.7-41
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• 2018

The projects of citizen science which is originated from citizen data collecting action driven by governmental institutes and science associations have been implemented with different form of collaboration with scientists. The themes of citizen science has extended from the ecology to astronomy, distributed computing, and particle physics. Citizen science could contribute to the advancement of science through cost-effective science research based on citizen volunteer data collecting. In addition, citizen science enhance the public understanding of science by increasing knowledge of citizen participants. The community-led citizen science projects could raise public awareness of environmental problems and promote the participation in environmental problem-solving. Citizen science projects based on local tacit knowledge can be of benefit to the local environmental policy decision making and implementation of policy. These social values of citizen science make many countries develop promoting policies of citizen science. The korean government also has introduced some citizen science projects. However there are some obstacles, such as low participation of citizen and scientists in projects which the government has to overcome in order to promote citizen science. It is important that scientists could recognize values of citizen science through the successful government driven citizen science projects and the evaluation tool of scientific career could be modified in order to promote scientist's participation. The project management should be well planned to intensify citizen participation. The government should prepare open data policy which could support a data reliability of the community-led monitoring projects. It is also desirable that a citizen science network could be made with the purpose of sharing best practices of citizen science.

• The Research Journal of the Costume Culture
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• v.26 no.2
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• pp.251-263
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• 2018

As mobile shopping has increased in the new media age, fashion consumers' decision making and product consumption processes have changed. The volume of consumer-driven information has expanded since media and social networking sites have enabled consumers to share information they obtain. The purpose of this study was to determine the factors affecting information searching strategies and information sharing about fashion products. An online survey collected data from 466 respondents, relating to the influence of product price level and consumer SNS commitment level on information search and information sharing. Experimental design of three product price level and two consumer SNS commitment level was used. Analysis of the data identified factors in fashion information searching as ongoing searching, prepurchase web portal information search, and prepurchase marketing information search. For low-price fashion products, prepurchase product-detail influenced intention to share information. For mid-priced products, ongoing search significantly affected intention to share information. Both ongoing search and prepurchase marketing information search showed significant effects for high-price products. Consumers who are more committed to SNS engaged in significantly more searching in all aspects of information search factors. Significant interaction effect was detected for consumer SNS commitment level and product price level. When consumers with low consumer SNS commitment search for information on lower-priced fashion products, they are less likely do a prepurchase web portal information search.