• 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.

• Korean Circulation Journal
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• v.53 no.7
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• pp.425-451
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• 2023

Most patients with heart failure (HF) have multiple comorbidities, which impact their quality of life, aggravate HF, and increase mortality. Cardiovascular comorbidities include systemic and pulmonary hypertension, ischemic and valvular heart diseases, and atrial fibrillation. Non-cardiovascular comorbidities include diabetes mellitus (DM), chronic kidney and pulmonary diseases, iron deficiency and anemia, and sleep apnea. In patients with HF with hypertension and left ventricular hypertrophy, renin-angiotensin system inhibitors combined with calcium channel blockers and/or diuretics is an effective treatment regimen. Measurement of pulmonary vascular resistance via right heart catheterization is recommended for patients with HF considered suitable for implantation of mechanical circulatory support devices or as heart transplantation candidates. Coronary angiography remains the gold standard for the diagnosis and reperfusion in patients with HF and angina pectoris refractory to antianginal medications. In patients with HF and atrial fibrillation, longterm anticoagulants are recommended according to the CHA₂DS₂-VASc scores. Valvular heart diseases should be treated medically and/or surgically. In patients with HF and DM, metformin is relatively safer; thiazolidinediones cause fluid retention and should be avoided in patients with HF and dyspnea. In renal insufficiency, both volume status and cardiac performance are important for therapy guidance. In patients with HF and pulmonary disease, beta-blockers are underused, which may be related to increased mortality. In patients with HF and anemia, iron supplementation can help improve symptoms. In obstructive sleep apnea, continuous positive airway pressure therapy helps avoid severe nocturnal hypoxia. Appropriate management of comorbidities is important for improving clinical outcomes in patients with HF.

• 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.

• Information Systems Review
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• v.21 no.1
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• pp.1-22
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• 2019

Mindfulness is the process of actively noticing new things. Today, companies have introduced and run mindfulness programs because the mindfulness has possible applications of productivity and innovation in corporation. However, role of mindfulness has not been clearly investigated in behavior research of Information System. The purpose of this study is to confirm the effects of mindfulness on technology acceptance process. Based on UTAUT Model, we examined how mindfulness in technology acceptance process moderate antecedent factors of acceptance intentions and use behavior. For empirical research, we conducted a survey on acceptance of smart watch of internet of things for employees of companies applying the mindfulness programs. then, we analyzed survey sample in empirical methodologies. Based on the empirical analysis, cognizance of alternative technologies in mindfulness factors increased the impact of performance expectancy on acceptance intention. Novelty seeking in mindfulness factors increased the impact of effort expectancy on acceptance intention. Awareness of local context in mindfulness factors decreased the impact of social influence on acceptance intention. engagement with technology in mindfulness factors increased the impact of facilitating conditions on use behavior. This study suggests academic implications and practical implications based on the results of the research. The implications will help to support and extend the theory of technology acceptance model while providing practical insights for IT acceptance by suggesting ways to utilize mindfulness in corporation.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.