• Journal of Yeungnam Medical Science
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• v.40 no.2
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• pp.156-163
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• 2023

Background: Interest in digital medical information has increased because it allows doctors to easily access a patient's medical records and provide appropriate medical care. Blockchain technology ensures data safety, reliability, integrity, and transparency by distributing medical data to all users over a peer-to-peer network. This study attempted to assess pediatricians' thoughts and attitudes toward introducing blockchain technology into the medical field. Methods: This study used a questionnaire survey to examine the thoughts and attitudes of 30- to 60-year-old pediatricians regarding the introduction of blockchain technology into the medical field. Responses to each item were recorded on a scale ranging from 1 (never agree) to 7 (completely agree). Results: The scores for the intentions and expectations of using blockchain technology were 4.0 to 4.6. Pediatricians from tertiary hospitals responded more positively (4.5-4.9) to the idea of using blockchain technology for hospital work relative to the general population (4.3-4.7). However, pediatricians working in primary and secondary hospitals had a slightly negative view of the application of blockchain technology to hospital work (p=0.018). Conclusion: When introducing the medical records of related pediatric and adolescent patients using blockchain technology in the future, it would be better to conduct a pilot project that prioritizes pediatricians in tertiary hospitals. The cost, policy, and market participants' perceptions are essential factors to consider when introducing technology in the medical field.

• Journal of the Korean Society of Physical Medicine
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• v.18 no.4
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• pp.155-162
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• 2023

PURPOSE: The primary objective of this study was to develop a virtual reality-based vestibular rehabilitation system to enhance balance perception, target rehabilitation specialists, and evaluate its usability. A key goal was establishing a system refinement strategy based on the collected data. METHODS: We conducted a study involving ten adults aged 10 to 29 in Gwangju Metropolitan City to evaluate the usability of a virtual reality-based vestibular rehabilitation system to enhance balance perception. After introducing the product and explaining its use to the participants, balance assessments and training were conducted using computerized dynamic posturography (CDP) (also called the test of balance [TOB]). Subsequently, participants were given a questionnaire to evaluate subjective stability, operability, and satisfaction. Frequency analysis was utilized to determine the frequency of the variable values of the measurement items in the survey for descriptive statistics. RESULTS: We found that the average usability score was 2.587. When broken down by category, stability received an average rating of 2.725, operability scored an average of 2.783, and satisfaction averaged 2.454. These findings suggest that most participants experienced positive sentiments and considerable satisfaction. CONCLUSION: The study successfully developed a virtual reality-based vestibular rehabilitation system, which was an improvement over the previous model and addressed its shortcomings. The results show that users with vestibular impairments are satisfied and more engaged with this system, indicating that additional studies are warranted.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.9-13
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• 2023

In this study, we explored the potential of integrating interactive AI callbot technology into the medical consultation domain as part of a broader service development initiative. Aimed at enhancing patient satisfaction, the AI callbot was designed to efficiently address queries from hospitals' primary users, especially the elderly and those using phone services. By incorporating an AI-driven callbot into the hospital's customer service center, routine tasks such as appointment modifications and cancellations were efficiently managed by the AI Callbot Agent. On the other hand, tasks requiring more detailed attention or specialization were addressed by Human Agents, ensuring a balanced and collaborative approach. The deep learning model for voice recognition for this study was based on the Transformer model and fine-tuned to fit the medical field using a pre-trained model. Existing recording files were converted into learning data to perform SSL(self-supervised learning) Model was implemented. The ANN (Artificial neural network) neural network model was used to analyze voice signals and interpret them as text, and after actual application, the intent was enriched through reinforcement learning to continuously improve accuracy. In the case of TTS(Text To Speech), the Transformer model was applied to Text Analysis, Acoustic model, and Vocoder, and Google's Natural Language API was applied to recognize intent. As the research progresses, there are challenges to solve, such as interconnection issues between various EMR providers, problems with doctor's time slots, problems with two or more hospital appointments, and problems with patient use. However, there are specialized problems that are easy to make reservations. Implementation of the callbot service in hospitals appears to be applicable immediately.

• Journal of the Korean Institute of Rural Architecture
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• v.25 no.4
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• pp.37-44
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• 2023

As a basic study to analyze the relative importance of external space in urban development projects, this study selects evaluation indicators for external space planning and then analyzes systematic external space planning through expert surveys. The scope of the study is to examine the criteria of evaluation items for external space derived from existing studies and to suggest the importance and priority of evaluation items. As a research method, we reviewed the legal and research literature on landscape planning and external space-related guidelines, and conducted a primary review of external space planning evaluation items analyzed by questionnaire. The reviewed items were again reviewed and selected through expert group discussions (FGI). The selected evaluation items were surveyed by expert groups and analyzed in depth using the hierarchical analysis method (AHP). Looking at the relative importance of the calculated sub-items, among the 17 sub-items, 'planning open space' (.096) is the largest, followed by 'pedestrianization' (.082), 'linking with adjacent buildings, streets, parks, and green areas' (.077), 'securing public space through various planning techniques such as linking with pedestrian paths' (.066), 'Plan the placement, form, and scale of buildings in consideration of the identity of the destination' (.065), 'Plan buildings, streets, parks, and green spaces in an integrated and holistic manner' (.065), 'Harmonize with the surrounding environment (landscape)' (.063), 'Harmonize with surrounding buildings and apply landscape planning in urban planning' (.063), 'Entrances and lower floors of buildings are planned as parks for users and pedestrians' (.060), 'Preserve and expand green areas and establish maintenance plans for urban greening' (.054), 'Form the basis for a comfortable life for urban residents by providing long-term development directions' (.047), 'Activate community activities and plan pedestrian environments and streetscapes considering human scale' (.047), 'Establish and propose basic directions for urban greening' (.046), 'Plan buildings, streets, parks, and green areas considering the hierarchy and characteristics of the landscape structure' (.045), 'Plan for integrated land use' (.045), 'Create green axes in connection without cutting them due to development activities' (.044), and 'Apply barrier free design' (.034).

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.23-28
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• 2024

The multi-tenancy and high scalability of the cloud have inspired businesses and organizations across various sectors to adopt and deploy cloud computing. Cloud computing provides cost-effective, reliable, and convenient access to pooled resources, including storage, servers, and networking. Cloud service models, SaaS, PaaS, and IaaS, enable organizations, developers, and end users to access resources, develop and deploy applications, and provide access to pooled computing infrastructure. Despite the benefits, cloud service models are vulnerable to multiple security and privacy attacks and threats. The SaaS layer is on top of the PaaS, and the IaaS is the bottom layer of the model. The software is hosted by a platform offered as a service through an infrastructure provided by a cloud computing provider. The Hypertext Transfer Protocol (HTTP) delivers cloud-based apps through a web browser. The stateless nature of HTTP facilitates session hijacking and related attacks. The Open Web Applications Security Project identifies web apps' most critical security risks as SQL injections, cross-site scripting, sensitive data leakage, lack of functional access control, and broken authentication. The systematic literature review reveals that data security, application-level security, and authentication are the primary security threats in the SaaS model. The recommended solutions to enhance security in SaaS include Elliptic-curve cryptography and Identity-based encryption. Integration and security challenges in PaaS and IaaS can be effectively addressed using well-defined APIs, implementing Service Level Agreements (SLAs), and standard syntax for cloud provisioning.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.1
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• pp.285-302
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• 2024

For this article, we conducted frequency analysis, topic modeling, and network analysis on eleven texts related to collection development policy found in the National Library of Korea. We deduced the main keywords related to collection development policies and analyzed the relationship between them. We subsequently conducted a pie coefficient analysis to identify the characteristics of collection development policies of university libraries and public libraries by category. The results showed that keywords such as "material," "library," "collection development," "user," and "collection" were the main keywords in frequency analysis and network centrality. Meanwhile, the pie coefficient analysis revealed that keywords such as "university," "construction," "student," "target," and "cost" were prevalent in university libraries, indicating that the academic needs of users and the discussion of digital resources were primary issues, while keywords related to the information needs of various user groups-including "adults," "survey," "feature," and "religion" -appeared in public libraries.

• Asian Journal for Public Opinion Research
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• v.12 no.1
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• pp.53-74
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• 2024

The proliferation of health misinformation gained momentum amidst the outbreak of the novel coronavirus disease 2019 (COVID-19). People stuck in their homes, without work pressure, regardless of health concerns towards personal, family, or peer groups, consistently demanded information. People became engaged with misinformation while attempting to find health information content. This study used the content analysis method and analyzed 1,154 misinformation stories from four prominent signatories of the International Fact-Checking Network during the pandemic. The study finds the five main categories of misinformation related to the COVID-19 pandemic. These are 1) the severity of the virus, 2) cure, prevention, and treatment, 3) myths and rumors about vaccines, 4) health authorities' guidelines, and 5) personal and social impacts. Various sub-categories supported the content characteristics of these categories. The study also analyzed the emotional valence of health misinformation. It was found that misinformation containing negative sentiments got higher engagement during the pandemic. Positive and neutral sentiment misinformation has less reach. Surprise, fear, and anger/aggressive emotions highly affected people during the pandemic; in general, people and social media users warning people to safeguard themselves from COVID-19 and creating a confusing state were found as the primary motivation behind the propagation of misinformation. The present study offers valuable perspectives on the mechanisms underlying the spread of health-related misinformation amidst the COVID-19 outbreak. It highlights the significance of discerning the accuracy of information and the feelings it conveys in minimizing the adverse effects on the well-being of public health.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.203-211
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• 2024

Utilizing programming languages for data visualization can enhance the efficiency and effectiveness in handling data volume, processing time, and flexibility. However, practice is required to become proficient in programming. Therefore public data-based the problem bank was developed to practice data visualization in a programming automatic assessment system. Public data were collected based on topics suggested in the curriculum and were preprocessed to make it suitable for users to visualize. The problem bank was associated with the mathematics curriculum to learn various data visualization methods. The developed problems were reviewed to expert and pilot testing, which validated the level of the questions and the potential of integrating data visualization in math education. However, feedback indicated a lack of student interest in the topics, leading us to develop additional questions using student-center data. The developed problem bank is expected to be used when students who have learned Python in primary school information gifted or middle school or higher learn data visualization.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.235-245
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• 2023

Smart applications based on the Network of Everything also known as Internet of Everything (IoE) are increasing popularity as network connectivity requires rise further. As a result, there will be a greater need for developing 6G technologies for wireless communications in order to overcome the primary limitations of visible 5G networks. Furthermore, implementing neural networks into 6G will bring remedies for the most complex optimizing networks challenges. Future 6G mobile phone networks must handle huge applications that require data and an increasing amount of users. With a ten-year time skyline from thought to the real world, it is presently time for pondering what 6th era (6G) remote correspondence will be just before 5G application. In this article, we talk about 6G dreams to clear the street for the headway of 6G and then some. We start with the conversation of imaginative 5G organizations and afterward underline the need of exploring 6G. Treating proceeding and impending remote organization improvement in a serious way, we expect 6G to contain three critical components: cell phones super broadband, very The Web of Things (or IoT and falsely clever (artificial intelligence). The 6G project is currently in its early phases, and people everywhere must envision and come up with its conceptualization, realization, implementation, and use cases. To that aim, this article presents an environment for Presented Distributed Artificial Intelligence as-a-Services (DAIaaS) supplying in IoE and 6G applications. The case histories and the DAIaaS architecture have been evaluated in terms of from end to end latency and bandwidth consumption, use of energy, and cost savings, with suggestion to improve efficiency.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.163-174
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• 2023

Purpose - This study examines the effect of consumers' motivations on the perception and purchase intentions of electric cars. Specifically, it empirically analyzes how moral motivations based on personal environmental values and norms in car usage and purchasing influence the perceived usefulness and purchase intentions of electric cars. Furthermore, it investigates whether the influence of moral motivations on perceived usefulness and purchase intentions varies according to the user's driving characteristics. Design/methodology/approach - An online survey was conducted with 234 respondents, by setting criteria for participants as car owners or primary car users within their households, ensuring the sample composition was not biased in terms of the presence or absence of experience with eco-friendly cars. Findings - The research findings indicate that perceived usefulness mediates the effect of consumers' moral motivations on their intention to purchase electric cars. The results of the moderating effect of driving distance on perceived usefulness revealed a significant interaction effect; however, there was no significant interaction effect on purchase intentions. Specifically, for individuals with shorter driving distances, as consumers' moral motivations increase, their perception of the usefulness of electric cars also increases. In contrast, for those with longer driving distances, the increase in perceived usefulness due to moral motivations shows a decreasing trend. Research implications or Originality - This study considered individual driving characteristics that previous research on electric vehicle adoption overlooked, and suggested that setting specific communicating points for electric cars according to driving distance levels might be effective. Lastly, it proposes directions for future research that motivations influencing eco-friendly vehicle purchases may differ based on driving characteristics