• Information Systems Review
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• v.20 no.2
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• pp.87-110
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• 2018

This study reviews previous studies about the effects of RFID capabilities on strategic supply chain competence and business performance in the Chinese context. This study introduces a new perspective that measures the degree to which RFID capability levels contribute to business performance. Such an assumption is based on the fact that companies build their own capabilities through RFID capabilities and that these capabilities provide a competitive advantage for enterprises. Data on all sorts of logistics, distribution, and manufacturing companies that introduced RFID system in China were collected for data analysis. This study analyzes the structural equation modeling using Smart-PLS 2.0 program. This study confirms that internal reliability, convergent validity, and discriminant validity are satisfied. The hypothesis test result on the relationship between RFID capacity and strategic supply chain competence and strategic supply chain competence and company results is partially adopted. This study aids in establishing a RFID system construction strategy to enhance supply chain competence by suggesting guidelines for the successful introduction of RFID system through identifying the causal relationship between RFID capacity and strategic supply chain competence. This study also suggests the influence of RFID competency on visibility, agility, flexibility, and collaborations.

• Knowledge Management Research
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• v.24 no.4
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• pp.195-218
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• 2023

This study empirically analyzes the effect of a sports club's performance and social media operations on online information search volume, reflecting fan engagement. Additionally, it confirms that such effect can vary depending on the issuance of sports fan tokens. The analysis of the data resulted in the support of all four hypotheses presented in this study. The team's goal differentials during the games exhibited a significant and positive effect on the online information search volume by fans. Furthermore, the quantity of a team's social media posts also showed a significant and positive effect on the online information search volume. The aforementioned effects of the team's game-related performance and social media activity on the online information search volume appeared to be strengthened when the sports fan tokens of the team were issued. This study conducts an empirical analysis of fan engagement in sports clubs and delves into the marketing dimensions of sports fan tokens. By doing so, it broadens the research scope within sports marketing and offers practical insights for the development of marketing strategies by sports clubs.

• Microbiology and Biotechnology Letters
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• v.51 no.4
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• pp.500-506
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• 2023

Carbapenem-resistant Klebsiella pneumoniae (CRKP) is emerging as a worldwide public health threat. Recently, Klebsiella pneumoniae carbapenemase-2 (KPC-2)-producing sequence type (ST) 307 was identified main clone of CRKP, and dissemination of ST307 was reported in South Korea. This study examined the molecular characteristic and antimicrobial resistance pattern of 50 CRKP isolated from a tertiary hospital in Daejeon, from March 2020 to December 2021. Epidemiological relationship was analyzed by Multilocus sequence typing (MLST) and antimicrobial susceptibility test was determined using disk-diffusion method. PCR and DNA sequence analysis were performed to identify carbapenemase genes. CRKP infections were significantly more frequent in males and the patients aged ≥ 60 years. Among the 50 CRKP isolates, 46 isolates (92.0%) were multidrug-resistant (MDR), and 44 isolates (88.0%) were carbapenemase-producing K. pneumoniae (CPKP). The major carbapenemase type was KPC-2 (36 isolates, 72.0%) and New Delhi metalloenzyme-1 (NDM-1) and NDM-5 were identified in 7 isolates (14.0%) and 1 isolate (2.0%), respectively. In particular, 88.9% (32/36) of KPC-2-producing K. pneumoniae belonged to ST307, whereas 87.5% (7/8) of NDM-1,-5-producing K. pneumoniae belonged to non-ST307. These results suggest that proper infection control and effective surveillance network need to prevent not olny the spread of ST307, but also the development of non-ST307.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.133-138
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• 2024

In the modern academic research environment, the advancement of digital technology provides researchers with increasingly diverse and rich access to information, but at the same time, the issue of author identification has emerged as a new challenge. The problem of author identification is a major factor that undermines the transparency and accuracy of academic communication, potentially causing confusion in the accurate attribution of research results and the construction of research networks. In response, identifier systems such as the International Standard Name Identifier (ISNI) and Open Researcher and Contributor ID (ORCID) have been introduced, but still face limitations due to low participation by authors and inaccurate entry of information. This study focuses on researching information management methods for identification from the moment author information is first entered into the system, proposing ways to improve the accuracy of author identification and maximize the efficiency of academic information services. Through this, it aims to renew awareness of the issue of author identification within the academic community and present concrete measures that related institutions and researchers can take to solve this problem.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.27-34
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• 2024

The direct and indirect damages caused by fires in underground utility tunnels have a great impact on society as a whole, so efforts are needed to prevent and manage them in advance. To this end, research is ongoing to prevent disasters such as fire flooding by applying digital twin technology to underground utility tunnels. A network is required to transmit the sensed signals from each sensor to the platform. In essence, it is necessary to analyze the application of wireless networks in the underground utility tunnel environments because the tunnel lacks the reception range of external wireless communication systems. Within the underground utility tunnels, electromagnetic interference caused by transmission and distribution cables, and diffuse reflection of signals from internal structures, obstacles, and metallic pipes such as water pipes can cause distortion or size reduction of wireless signals. To ensure real-time connectivity for remote surveillance and monitoring tasks through sensing, it is necessary to measure and analyze the wireless coverage in underground utility tunnels. Therefore, in order to build a wireless network environment in the underground utility tunnels. this study minimized the shaded area and measured the actual cavity environment so that there is no problem in connecting to the wireless environment inside the underground utility tunnels. We analyzed the data transmission rate, signal strength, and signal-to-noise ratio for each section of the terrain of the underground utility tunnels. The obtained results provide an appropriate wireless planning approach for installing wireless networks in underground utility tunnels.

• The Korean Journal of Archival Studies
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• no.79
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• pp.33-82
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• 2024

Interest in ESG management, which spread through the UN PRI in 2006, has recently spread throughout our society. Consumers use a company's activeness in the ESG field as the standard of consumption behavior, and the international community is reorganizing and strengthening various regulatory measures. In the investment market, non-financial performance (ESG information) is used as an important investment indicator along with financial performance (credit rating). Due to these changes in the corporate evaluation paradigm and market pressure, if a company neglects ESG response activities, it is more likely to be excluded from market selection, and accordingly, the importance of ESG management is also increasing. Companies are making various efforts to secure legitimacy in response to these market pressures, but in the process, it is difficult to systematically manage and utilize records/data that are the basis for ESG management. For a basic understanding of ESG management, this paper summarizes the emerging process of ESG and the current ESG-related regulations applied to companies. Through this, it can be seen that ESG management is not carried out with the good will of the company, but is accepted as a management strategy for the survival of the company according to the change in the corporate evaluation paradigm. Through interviews with the company's ESG-related personnel, the company's ESG response process was divided into passive communication and active communication, and the problems identified during the interview were summarized for each communication type. In addition, in the process of passively and actively communicating ESG management information with internal and external stakeholders, the possibility that ESG archives can function as a tool to overcome problems for each communication type was raised, and five types of ESG archives that can play this role were presented.

• Advanced Industrial SCIence
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• v.3 no.1
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• pp.23-29
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• 2024

In this scholarly investigation, the focus is placed on the transformative potential of edge computing in enhancing Intelligent Transportation Systems (ITS) for the facilitation of autonomous driving. The intrinsic capability of edge computing to process voluminous datasets locally and in a real-time manner is identified as paramount in meeting the exigent requirements of autonomous vehicles, encompassing expedited decision-making processes and the bolstering of safety protocols. This inquiry delves into the synergy between edge computing and extant ITS infrastructures, elucidating the manner in which localized data processing can substantially diminish latency, thereby augmenting the responsiveness of autonomous vehicles. Further, the study scrutinizes the deployment of edge servers, an array of sensors, and Vehicle-to-Everything (V2X) communication technologies, positing these elements as constituents of a robust framework designed to support instantaneous traffic management, collision avoidance mechanisms, and the dynamic optimization of vehicular routes. Moreover, this research addresses the principal challenges encountered in the incorporation of edge computing within ITS, including issues related to security, the integration of data, and the scalability of systems. It proffers insights into viable solutions and delineates directions for future scholarly inquiry.

• Knowledge Management Research
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• v.25 no.1
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• pp.67-88
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• 2024

Smart tourism aims to maximize the utilization of local tourism resources, effectively manages cities and contributes to improving communication and quality of life between tourists and residents. Therefore, smart tourism emphasizes synergistic collaboration, considering both residents and tourists. This study explores smart tourism interaction and roles in enhancing regional competitiveness. By conducting thorough examination, focusing on integrating the four key elements of smart tourism city (smart experience, smart convenience, smart accessibility, and smart platform) with local residents, local businesses, regional resources, and ecosystem to foster positive synergies, Incheon smart tourism city project was employed as a single case study design. Research results indicate that the collaborative model of a smart tourism city positively impacts service satisfaction and strengthens regional tourism competitiveness. Building upon these results, this study aims to contribute to the development of smart tourism cities by proposing directions for future development and emphasizing the enhancement of regional competitiveness through the integration of smart technology and local tourism.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.2
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• pp.147-156
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• 2024

The sustainable management and enhancement of marine resources are becoming increasingly important issues worldwide. This study was conducted in response to these challenges, focusing on the development and performance comparison of fish detection and classification models as part of a deep learning-based technique for assessing the effectiveness of marine resource enhancement projects initiated by the Korea Fisheries Resources Agency. The aim was to select the optimal model by training various sizes of YOLOv8-Seg models on a fish image dataset and comparing each performance metric. The dataset used for model construction consisted of 36,749 images and label files of 12 different species of fish, with data diversity enhanced through the application of augmentation techniques during training. When training and validating five different YOLOv8-Seg models under identical conditions, the medium-sized YOLOv8m-Seg model showed high learning efficiency and excellent detection and classification performance, with the shortest training time of 13 h and 12 min, an of 0.933, and an inference speed of 9.6 ms. Considering the balance between each performance metric, this was deemed the most efficient model for meeting real-time processing requirements. The use of such real-time fish detection and classification models could enable effective surveys of marine resource enhancement projects, suggesting the need for ongoing performance improvements and further research.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.205-212
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• 2023

Among cardiac diseases, arrhythmias can lead to serious complications such as stroke, heart attack, and heart failure if left untreated, so continuous and accurate ECG monitoring is crucial for clinical care. However, the accurate interpretation of electrocardiogram (ECG) data is entirely dependent on medical doctors, which requires additional time and cost. Therefore, this paper proposes an arrhythmia recognition module for the purpose of developing a medical platform through the analysis of abnormal pulse waveforms based on Lifelogs. The proposed method is to convert ECG data into image format instead of time series data, apply visual pattern recognition technology, and then detect arrhythmia using CNN model. In order to validate the arrhythmia classification of the CNN model by image type conversion of ECG data proposed in this paper, the MIT-BIH arrhythmia dataset was used, and the result showed an accuracy of 97%.