• 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.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.37-64
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• 2022

As the social acceptance of artificial intelligence increases, the number of cases of applying machine learning methods to companies is also increasing. Technical factors such as accuracy and interpretability have been the main criteria for selecting machine learning methods. However, the success of implementing machine learning also affects management factors such as IT departments, operation departments, leadership, and organizational culture. Unfortunately, there are few integrated studies that understand the success factors of machine learning selection in which technical and management factors are considered together. Therefore, the purpose of this paper is to propose and empirically analyze a technology-management integrated model that combines task-tech fit, IS Success Model theory, and John Rice's algorithm selection process model to understand machine learning selection within the company. As a result of a survey of 240 companies that implemented machine learning, it was found that the higher the algorithm quality and data quality, the higher the algorithm-problem fit was perceived. It was also verified that algorithm-problem fit had a significant impact on the organization's innovation and productivity. In addition, it was confirmed that outsourcing and management support had a positive impact on the quality of the machine learning system and organizational cultural factors such as data-driven management and motivation. Data-driven management and motivation were highly perceived in companies' performance.

• Korean Journal of School Psychology
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• v.16 no.3
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• pp.401-431
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• 2019

This study explored the lived experiences of high school students who experienced a norm-referenced evaluation with the Naesin system. The participants were 15 high school students who resided in the areas of Seoul, Gyeonggi, and Busan. This study adopted a phenomenological research method, which is developed by Giorgi. The study resulted in 370 meaning units, 71 summaries of meaning units, 26 sub-constituents, and 9 constituents. The results showed that participants experienced their relationships with classmates were centered around competitions and they experienced the sense of repeated frustration with their academic goals. Participants perceived that their personal values equated with their academic rankings and they anticipated academic rankings becoming their future social rankings. Low rankings with good performance, learning for exam, and unfair treatment in school made them realize that the education is not for learning but for differentiating students. Participants have found the ways to know better about reality and self-regulated their thoughts and emotions. Further, this study identified resilient aspects of the participants such as support from parents and teachers and hopeful thoughts. This study discussed the meaning of the findings and implications of the findings.

• Knowledge Management Research
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• v.24 no.3
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• pp.53-71
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• 2023

Environmental, Social, and Governance (ESG) refers to factors that are important for assessing a firm's social and environmental effect, as well as its governance standards. This paper investigates the relationship between ESG-based corporate governance and SDGs strategy implementation by discussing about incorporating ESG issues into corporate operations. It digs into the advantages and disadvantages of aligning corporate governance with the SDGs, demonstrating the potential for delivering long-term value for both firms and society as a whole. In this paper, we investigate ESG-Based Knowledge Management (ESG-KM), a knowledge management system that incorporates sustainability principles. More specifically, the paper investigates how the synergy between ESG-KM and ESG-Based Corporate Governance (ESG-CG) might influence firms' long-term value creation, stakeholder involvement, and sustainable decision-making. Finally, this paper investigates how public organizations might use knowledge management to improve the implementation and effect of ESG-CG principles, resulting in better sustainable outcomes. Public enterprises may support responsible decision-making, increase stakeholder involvement, and achieve long-term performance by linking ESG principles with corporate governance standards. The paper then explores how ESG-KM might help public firms integrate these concepts into their governance structures. The scientific novelty of this paper resides in its thorough investigation, realistic implementation methodologies, and novel combination of ESG principles, corporate governance, and knowledge management. Furthermore, by providing actionable insights and emphasizing the application of these concepts in the context of public enterprises, the paper makes a valuable contribution to the field of management, propelling the discourse on responsible and sustainable business practices in both the private and public sectors.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.1-10
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• 2023

This paper proposes a method to extend Inter-Carrier Interference (ICI) canceling Orthogonal Frequency Division Multiplexing (OFDM) receivers for 5G mobile systems to spatial multiplexing 2×2 MIMO (Multiple Input Multiple Output) systems to support high-speed ground transportation services by linear motor cars traveling at 500 km/h. In Japan, linear-motor high-speed ground transportation service is scheduled to begin in 2027. To expand the coverage area of base stations, 5G mobile systems in high-speed moving trains will have multiple base station antennas transmitting the same downlink (DL) signal, forming an expanded cell size along the train rails. 5G terminals in a fast-moving train can cause the forward and backward antenna signals to be Doppler-shifted in opposite directions, so the receiver in the train may have trouble estimating the exact channel transfer function (CTF) for demodulation. A receiver in such high-speed train sees the transmission channel which is composed of multiple Doppler-shifted propagation paths. Then, a loss of sub-carrier orthogonality due to Doppler-spread channels causes ICI. The ICI Canceller is realized by the following three steps. First, using the Demodulation Reference Symbol (DMRS) pilot signals, it analyzes three parameters such as attenuation, relative delay, and Doppler-shift of each multi-path component. Secondly, based on the sets of three parameters, Channel Transfer Function (CTF) of sender sub-carrier number n to receiver sub-carrier number l is generated. In case of n≠l, the CTF corresponds to ICI factor. Thirdly, since ICI factor is obtained, by applying ICI reverse operation by Multi-Tap Equalizer, ICI canceling can be realized. ICI canceling performance has been simulated assuming severe channel condition such as 500 km/h, 8 path reverse Doppler Shift for QPSK, 16QAM, 64QAM and 256QAM modulations. In particular, 2×2MIMO QPSK and 16QAM modulation schemes, BER (Bit Error Rate) improvement was observed when the number of taps in the multi-tap equalizer was set to 31 or more taps, at a moving speed of 500 km/h and in an 8-pass reverse doppler shift environment.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.130-144
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• 2023

Recently, various positioning technologies are being researched based on signal-based positioning and image-based positioning to obtain accurate indoor location information. Among these, various studies are being conducted on image positioning technology that determines the location of a mobile terminal using images acquired through cameras and sensor data collected as needed. For video-based positioning, a method of determining indoor location is used by matching mobile terminal photos with virtual landmark images, and for this purpose, it is necessary to build indoor spatial information about various landmarks such as billboards, vending machines, and ATM machines. In order to construct indoor spatial information on various landmarks, a panoramic image in the form of a road view and accurate 3D survey results were obtained through c 13 buildings of the Electronics and Telecommunications Research Institute(ETRI). When comparing the 3D total station final result and the terrestrial lidar panoramic image coordinates, the coordinates and distance performance were obtained within about 0.10m, confirming that accurate landmark construction for use in indoor positioning was possible. By utilizing these terrestrial lidar achievements to perform 3D landmark modeling necessary for image positioning, it was possible to more quickly model landmark information that could not be constructed only through 3D modeling using existing as-built drawings.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.437-447
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• 2023

By actively adopting technologies from the Fourth Industrial Revolution, the port industry is trending toward new types of ports, such as automated and smart ports. However, behind the development of these ports, there is an increasing risk of cyber security incidents and threats within ports and container terminals, including information leakage through cargo handling equipment and ransomware attacks leading to disruptions in terminal operations. Despite the necessity of research to enhance cyber security within ports, there is a lack of such studies in the domestic context. This study focuses on Busan Port, a representative port in South Korea that actively incorporates technology from the Fourth Industrial Revolution, in order to discover variables for improving cyber security in container terminals. The research results categorized factors for enhancing cyber security in Busan Port's container terminals into network construction and policy support, standardization of education and personnel training, and legal and regulatory factors. Subsequently, multiple regression analysis was conducted based on these factors, leading to the identification of detailed factors for securing and enhancing safety, reliability, performance, and satisfaction in Busan Port's container terminals. The significance of this study lies in providing direction for enhancing cyber security in Busan Port's container terminals and addressing the increasing incidents of cyber security attacks within ports and container terminals.

• Journal of Korean Library and Information Science Society
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• v.55 no.1
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• pp.69-97
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• 2024

It is important to plan and operate various training programs at the national level to develop librarians' job performance expertise and future-oriented capabilities. The purpose of this study was to examine the possibility of introducing a librarian learning community as an training program at a professional education and training institution and to suggest an appropriate operation method. To this end, research was conducted using the following contents and methods: 1) theoretical discussion on program operation such as the concept, operation stages, and types of a librarian learning community through a review of related literature; 2) exploring the possibility of operating a librarian learning community through pilot operation and derivation of implications, 3) proposal of a librarian learning community operation model. This study reviewed the librarian learning community operating model through participant observation and participant opinion collection during the pilot operation process to minimize confusion in the early stages of implementation, and also presented an operational roadmap and support system for the successful establishment of the program in the future. There is a need to further develop the librarian learning community operating model presented in this study through implementation and empirical analysis over the next several years. However, the results of this study will also be useful as an initial operating model for a learning community for professional education and training in other fields.

• Journal of The Korean Association For Science Education
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• v.27 no.9
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• pp.907-918
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• 2007

This study was conducted to explore key factors of expertise development of talented scientists who achieved outstanding research performance according to the stages of expertise development and dimensions of individual-domain-field. To fulfill the research purpose, 31 domestic scientists who were awarded major prizes in the field of science were interviewed in-depth from March to September, 2007. Stages of expertise development were analyzed in light of Csikszentmihalyi's IDFI (individual-domain-field interaction) model. Self-directed learning, multiple interests and finding strength, academic and liberal home environment, and meaningful encounter were major factors affecting expertise development in the exploration stage. In the beginner stage, independence, basic knowledge on major, and thirst for knowledge at university affected expertise development. Task commitment, finding flow, finding their field of interest and lifelong research topic, and mentor in formal education were the affecting factors in the competent stage. Finally, placing priority, communication skills, pioneering new domain, expansion of the domain, and evaluation and support system affected talented scientists' expertise development in the leading stage. The meaning of major patterns of expertise development were analyzed and described. Based on these analyses, educational implications for nurturing scientists were suggested.

• Journal of Science Education
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• v.48 no.1
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• pp.1-14
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• 2024

The Korean Science Education Standards (KSES) were developed to support the establishment of a domestic national science curriculum to respond to future social and environmental changes as an action plan to improve scientific literacy in the context of science education. In this study, we analyzed the relationship between KSES and the 2022 revised middle science curriculum focusing its learning contents and learning objectives and sought effects of the successful implementation of the curriculum. As a result, the content system of the 2022 revised middle science curriculum was highly related to the categories of knowledge in KSES. Attempts to deal with the content related to the nature of science was also confirmed through content elements in science and society domains. In the case of achievement standards, it was focused on some areas of the performance expectations in KSES, but the level of statement of the achievement standards closely matched the level of middle school students as suggested by KSES. From these results, it was possible to confirm the high relationship between the 2022 revised middle science curriculum and KSES, as well as the possibility of using KSES as an international indicator for establishing future science education plans.