• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.287-297
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• 2020

The research aims to investigate the impact levels of determinants on the loyalty of accountants to FDI firms underlying investment management in Thanglong Industrial Park in Hanoi, Vietnam. We conducted a questionnaire consisting of 31 observation variables with a 5-point Likert scale. Independent variables were measured from 1 "without effect" to 5 "strongly". The method of data collection was done through the survey and subjects are accountants in FDI firms doing business in Thanglong Industrial Park in Hanoi. After checking the information on the votes, there are 120 questionnaires with full information for data entry and analysis, This study employs Cronbach's Alpha test, and regression model. The results show that seven determinants including Working environment, The characteristics of working; Training, promotion prospects and development; Income, Personal characteristic, Collective work together and The method of leading had positive relationships with the loyalty of accountants. Based on the findings, some recommendations are given related to such determinants to improve the loyalty of accountants of FDI firms in general and FDI firms in Thanglong Industrial Park in Hanoi in particular. With which, those firms can enhance performance, reduce financial strain, saving on investment in the recruiting process of new staff, increase profitability to ensure investment management.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.23-31
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• 2020

As children's participation in online activities has recently increased, online services for children are also rapidly increasing, but children are not sufficiently guaranteed their rights. The purpose of this study is to classify and analyze issues related to the children's online privacy issues in Korea through the current status and case studies of application services mainly used by children. For this purpose, this research analyzed problems related to the children's online privacy protection according to the stage of using the application. As a result of the application content analysis, 1) issues of child identification, 2) effectiveness of notice and consent, and 3) issues of children's rights as subjects of information were derived. Based on the current status analysis, the policy implications were drawn based on the children's online privacy protection in the online environment, and suggestions were made for improvement.

• The Journal of Information Systems
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• v.23 no.1
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• pp.161-184
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• 2014

Our study measures the Digital Life Index (DLI) of baby boomers by considering the utilization of digital devices in their everyday life. The study was conducted by implementing the following three-step approach: (1) development of survey questions and data collection; (2) build Digital Life Index (DLI) model and lastly; (3) empirical analysis using the Digital Life Index (DLI). In the first stage in order to develop the survey questions to measure the digital index, two surveys were conducted. For the first preliminary survey, it was done based on the existing literatures which enabled this investigation through FGI analysis involving real professionals. The second survey was conducted by commissioning a specialized external firm. In this survey, a total of 400 data was collected to verify the validity and objectivity of the data sample. The data gathered through the survey questions was used to develop the digital index. Firstly, the appropriate factors were extracted by conducting factor analysis. This factor analysis validates and verifies the factors which are appropriate in measuring Digital Life Index (DLI). The derived factors are broadly divided into five main factors. The first factor describes the possession, purchase and use of digital device (x1). Meanwhile, the second factor describes the digital device's software (x2) and the third factor describes the participation in utilizing digital device (x3). The fourth factor describes the utilization of digital device in human personal relationship (x4) and lastly, the fifth factor describes the effect of digital device in everyday life and work environment (x5). Secondly, the digital index model was developed. The variables to represent the Digital Life Index (DLI) are ${\chi}1t,{\chi}2t,{\chi}3t,{\chi}4t$ and ${\chi}5t$. Furthermore, as experience in using the digital index grows overtime, the growth can be represented by the "S" shape. Based on the results, Digital Life Index(DLI) is distributed with the highest point at 90.3 and the lowest point at 25.9.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2086-2097
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• 2021

The current cultural assets are being restored depending on the opinions of experts (craftsmen). We intend to introduce digitalized artificial intelligence techniques, excluding the personal opinions of experts on reconstruction of such cultural properties. The first step toward restoring digitized cultural properties is separation. The restoration of cultural properties should be reorganized based on recorded documents, period historical backgrounds and regional characteristics. The cultural properties in the form of photographs or images should be collected by separating the background. In addition, when restoring cultural properties most of them depend a lot on the tendency of the restoring person workers. As a result, it often occurs when there is a problem in the accuracy and reliability of restoration of cultural properties. In this study, we propose a search method for learning stored digital cultural assets using AI technology. Pagoda was selected for restoration of Cultural Properties. Pagoda data collection was collected through the Internet and various historical records. The pagoda data was classified by period and region, and grouped into similar buildings. The collected data was learned by applying the well-known CNN algorithm for artificial intelligence learning. The pagoda search used Yolo Marker to mark the tower shape. The tower was used a total of about 100-10,000 pagoda data. In conclusion, it was confirmed that the probability of searching for a tower differs according to the number of pagoda pictures and the number of learning iterations. Finally, it was confirmed that the number of 500 towers and the epochs in training of 8000 times were good. If the test result exceeds 8,000 times, it becomes overfitting. All so, I found a phenomenon that the recognition rate drops when the enemy repeatedly learns more than 8,000 times. As a result of this study, it is believed that it will be helpful in data gathering to increase the accuracy of tower restoration.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.91-97
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• 2022

The purpose of this study is to investigate the meaning and essence of nursing students' experience of handwashing education volunteer program. There were 10 students who participated in the handwashing education service, and data collection was conducted for two months from October to November 2021, and three focus groups were formed and interviewed. Data were analyzed by Colaizz's phenomenological research method. As a result of the study, 3 themes and 10 sub-themes were derived. The three themes were 'personal development', 'self-esteem as a pre-nursing nurse', and 'knowing the meaning of service'. Nursing students learned the meaning of service through handwashing education service, and it was found that they could experience their own inner maturity. Nursing students could see that it was a time to learn the true meaning of service through handwashing education volunteering. The results of this study provided an understanding of the educational service of nursing college students, which can be applied to the diversification of educational service programs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.725-734
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• 2024

The rapidly growing metaverse environment has received widespread attention across various fields such as health and medicine, culture and gaming, as well as politics. However, the excessive collection of personal data by the diverse sensors and devices used in the metaverse environment poses a substantial threat to user privacy. In this paper, we investigate existing cases of secure Multi-Party Computation(MPC) applications, examine the services anticipated to be necessary for the expansion of the metaverse environment, and analyze the privacy issues present in the metaverse environment as well as the limitations of current real-world services. Based on these findings, we propose application scenarios that utilize MPC to preserve user privacy in the metaverse environment. These proposed MPC application scenarios present a new perspective in metaverse security research. In the future, they are expected to be utilized in the development of secure metaverse services.

• The Korean Society of Law and Medicine
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• v.21 no.3
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• pp.145-178
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• 2020

This paper examines discussions surrounding cognitive liberty, neuro-privacy, and mental integrity from the perspective of Neuro-rights. The right to control one's neurological data entails self-determination of collection and usage of one's data, and the right to object to any way such data may be employed to negatively impact oneself. As innovations in neurotechnologies bear benefits and downsides, a novel concept of the neuro-rights has been suggested to protect individual liberty and rights. In Oct. 2020, the Chilean Senate presented the 'Proyecto de ley sobre neuroderechos' to promote the recognition and protection of neuro-rights. This new bill defines all data obtained from the brain as neuronal data and outlaws the commerce of this data. Neurotechnology, especially when paired with big data and artificial intelligence, has the potential to turn one's neurological state into data. The possibility of inferring one's intent, preferences, personality, memory, emotions, and so on, poses harm to individual liberty and rights. However, the collection and use of neural data may outpace legislative innovation in the near future. Legal protection of neural data and the rights of its subject must be established in a comprehensive way, to adapt to the evolving data economy and technical environment.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Archives of design research
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• v.17 no.2
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• pp.413-424
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• 2004

This paper defines the telepresence as a particular type of experience, rather than a collection of hardware. Defining telepresence in this way provides a means for examining telepresence in relation to other types of mediated experience. Presence refers to the natural perception of an environment, and telepresence refers to the mediated perception of an environment. Factors influencing whether a particular mediated environment will induce a sense of telepresence include the following: the combination of sensory stimuli employed in the environment, the ways in which participants are able to interact with the environment, and the characteristics of the individual experiencing the environment. Telepresence art invites the people from remote worlds to networked cyber space and creates the experience of 'being there' by making participants control the virtual reality system and receive feedback from their teleactions. It is the way to produce an open and engaging experience that manifests the cultural changes brought about by remote control, remote vision, telekinesis, and real-time exchange of audiovisual information. The principal determinants of telepresence are sensory immersion, sensory fidelity, cognitive fidelity and personal factors. This paper applies the 4 determinants to telepresence art works such as Ken Goldberg's Telegarden, Monika Fleischmann & Wolfgang Strauss' The Home of the Brain, Paul Sermon's Telematic Dreaming, Telematic Vision, Eduardo Kac's Uriapuru, Simon Penny's Traces and Paul Sermon & Andrea Zapp's A Body of Water.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.113-120
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• 2023

The purpose of this study was the accuracy of cardiac compression, fatigue, and physiological changes of the rescuer for different mask type in cardiopulmonary resuscitation(CPR). Data collection was from 9 to 12 May 2022, the participants were a total of 24 paramedic students with a BLS provider at D University. The students participated in an experiment in which 12 students each wore a surgical mask (Dental mask) and a fine particle 94% blocking mask (KF94 mask) and performed CPR for 2 minutes over a total of 7 times. As a result of the study, in the analysis of the quality of the rescuer's chest compression according to the type of mask, there was a significant difference in the compression speed (F=24.91, p<.001) and bad compression hand position (F=14.54, p=.024) in the group wearing the KF94, Fatigue showed significant differences in both the Dental mask group (F=51.16, p<.001) and the KF94 mask group (F=63.49, p<.001). Among the physiological changes, heart rate showed a significant difference between the Dental mask group (F=34.79, p<.001) and the KF94 mask group (F=35.55, p<.001), and the respiratory rate showed a significant difference between the Dental mask group (F=25.02, p=.001) and the KF94 mask group(F=23.02, p=.002). Therefore, in order to improve the quality of efficient chest compression and reduce the fatigue and physiological changes of rescuers, it will be necessary for rescuers to wear suitable personal protective equipment.