• Title/Summary/Keyword: network-based business

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Online Information Sources of Coronavirus Using Webometric Big Data (코로나19 사태와 온라인 정보의 다양성 연구 - 빅데이터를 활용한 글로벌 접근법)

  • Park, Han Woo;Kim, Ji-Eun;Zhu, Yu-Peng
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.11
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    • pp.728-739
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    • 2020
  • Using webometric big data, this study examines the diversity of online information sources about the novel coronavirus causing the COVID-19 pandemic. Specifically, it focuses on some 28 countries where confirmed coronavirus cases occurred in February 2020. In the results, the online visibility of Australia, Canada, and Italy was the highest, based on their producing the most relevant information. There was a statistically significant correlation between the hit counts per country and the frequency of visiting the domains that act as information channels. Interestingly, Japan, China, and Singapore, which had a large number of confirmed cases at that time, were providing web data related to the novel coronavirus. Online sources were classified using an N-tuple helix model. The results showed that government agencies were the largest supplier of coronavirus information in cyberspace. Furthermore, the two-mode network technique revealed that media companies, university hospitals, and public healthcare centers had taken a positive attitude towards online circulation of coronavirus research and epidemic prevention information. However, semantic network analysis showed that health, school, home, and public had high centrality values. This means that people were concerned not only about personal prevention rules caused by the coronavirus outbreak, but also about response plans caused by life inconveniences and operational obstacles.

Implementation of the ZigBee-based Homenetwork security system using neighbor detection and ACL (이웃탐지와 ACL을 이용한 ZigBee 기반의 홈네트워크 보안 시스템 구현)

  • Park, Hyun-Moon;Park, Soo-Hyun;Seo, Hae-Moon
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.46 no.1
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    • pp.35-45
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    • 2009
  • In an open environment such as Home Network, ZigBee Cluster comprising a plurality of Ato-cells is required to provide intense security over the movement of collected, measured data. Against this setting, various security issues are currently under discussion concerning master key control policies, Access Control List (ACL), and device sources, which all involve authentication between ZigBee devices. A variety of authentication methods including Hash Chain Method, token-key method, and public key infrastructure, have been previously studied, and some of them have been reflected in standard methods. In this context, this paper aims to explore whether a new method for searching for neighboring devices in order to detect device replications and Sybil attacks can be applied and extended to the field of security. The neighbor detection applied method is a method of authentication in which ACL information of new devices and that of neighbor devices are included and compared, using information on peripheral devices. Accordingly, this new method is designed to implement detection of malicious device attacks such as Sybil attacks and device replications as well as prevention of hacking. In addition, in reference to ITU-T SG17 and ZigBee Pro, the home network equipment, configured to classify the labels and rules into four categories including user's access rights, time, date, and day, is implemented. In closing, the results demonstrates that the proposed method performs significantly well compared to other existing methods in detecting malicious devices in terms of success rate and time taken.

Activating Local Society Resource Network of Social Business : Focusing on Kwangju and Jejudo (사회적기업의 지역사회 자원연계 활성화를 위한 사례연구 -광주광역시·제주특별자치도를 중심으로-)

  • Choi, Hyuk-Ra;Kim, Seon-Myung;Kim, Gi-Hyeon
    • The Journal of the Korea Contents Association
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    • v.12 no.1
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    • pp.308-317
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    • 2012
  • In this study, we searched for ways of the demand, the building up of strategic, collaborative networks plan activation of the local area network status by the current social enterprise and the direction of the future resources rinks, conducted by a case study of the (preliminary) social enterprise network-building activities based in Gwangju Metropolitan City and Jeju Special Self-Governing Province. By the study findings, local resources that the two regions social enterprise wants to connect are the most numerous in enterprise, public agencies and local media, followed by professionals' pro bo no, private organizations, volunteer groups. Hope for Information in conjunction is revealed in order by purchasing items, labor and financial support, public relations, purchasing service, marketing and a joint venture. For the conjunction, participating related events, the assistance of government agencies and related organizations joined, the role of chief engineer are emerged in order while they are performing work. By the findings, for the activation of local resources links of the social enterprises, it is necessary to impelled cooperation system between activating local profit companies, universities and one company ; a social enterprise and to uncovered volunteer activities of the community. Also, sparking, solidarity and building trust for social enterprises are derived as a ethical and alternative consumer movement.

Analysis of Domestic SNA-based Governance Study Trends (소셜네트워크분석을 통한 국내 거버넌스 연구 동향 분석)

  • Kim, Na-Rang;Choi, Hyung-Rim;Lee, Taihun
    • Journal of Digital Convergence
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    • v.16 no.7
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    • pp.35-45
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    • 2018
  • Research on the establishment of new governance aimed at efficient policy planning and the implementation thereof by the government has been conducted in response to social changes. Nonetheless, governance is comprehensive and encompasses different meanings; it takes various forms in the process of its actual application. Therefore, systematic classification of research on governance and analysis on its research trend are required. Accordingly, three researchers who majored in policy sciences, business informatics, and library and information science, respectively, searched for theses related to governance published since 2016 from Research Information Sharing Service and conducted a social network analysis (SNA) on them. According to their research results, the main research topics were largely classified into collaborative governance and local governance. Keywords throughout the topics included network, participation, conflict, and trust in line with the characteristics of governance. Representative subjects of governance included education, urban regeneration, and the environment. Further, measurement of betweenness centrality showed local governance was a main topic for convergent research. This study will lead to a greater understanding of research on governance and help activate such research. One limitation of this study is that it analyzed only theses with the keywords but not all theses on governance. Follow-up research should analyze all theses on governance and statistically verify them with SNA indexes.

Research Trends and Knowledge Structure of Digital Transformation in Fashion (패션 영역에서 디지털 전환 관련 연구동향 및 지식구조)

  • Choi, Yeong-Hyeon;Jeong, Jinha;Lee, Kyu-Hye
    • Journal of Digital Convergence
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    • v.19 no.3
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    • pp.319-329
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    • 2021
  • This study aims to investigate Korean fashion-related research trends and knowledge structures on digital transformation through information-based approaches. Accordingly, we first identified the current status of the relevant research in Korean academic literature by year and journal; subsequently, we derived key research topics through network analysis, and then analyzed major research trends and knowledge structures by time. From 2010 to 2020, we collected 159 studies published on Korean academic platforms, cleansed data through Python 3.7, and measured centrality and network implementation through NodeXL 1.0.1. The results are as follows: first, related research has been actively conducted since 2016, mainly concentrated in clothing and art areas. Second, the online platform, AR/VR, appeared as the most frequently mentioned topic, and consumer psychological analysis, marketing strategy suggestion, and case analysis were used as the main research methods. Through clustering, major research contents for each sub-major of clothing were derived. Third, major subject by period was considered, which has, over time, changed from consumer-centered research to strategy suggestion, and design development research of platforms or services. This study contributes to enhancing insight into the fashion field on digital transformation, and can be used as a basic research to design research on related topics.

Social Network Analysis of Long-term Standby Demand for Special Transportation (특별교통수단 장기대기수요에 대한 사회 연결망 분석)

  • Park, So-Yeon;Jin, Min-Ha;Kang, Won-Sik;Park, Dae-Yeong;Kim, Keun-Wook
    • Journal of Digital Convergence
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    • v.19 no.5
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    • pp.93-103
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    • 2021
  • The special means of transportation introduced to improve the mobility of the transportation vulnerable met the number of legal standards in 2016, but lack of development in terms of quality, such as the existence of long waiting times. In order to streamline the operation of special means of transportation, long-term standby traffic, which is the top 25% of the wait time, was extracted from the Daegu Metropolitan Government's special transportation history data, and spatial autocorrelation analysis and social network analysis were conducted. As a result of the analysis, the correlation between the average waiting time of special transportation users and the space was high. As a result of the analysis of internal degree centrality, the peak time zone is mainly visited by general hospitals, while the off-peak time zone shows high long-term waiting demand for visits by lawmakers. The analysis of external degree centrality showed that residential-based traffic demand was high in both peak and off-peak hours. The results of this study are considered to contribute to the improvement of the quality of the operation of special transportation means, and the academic implications and limitations of the study are also presented.

Emotion Recognition System Using Neural Networks in Textile Images (신경망을 이용한 텍스타일 영상에서의 감성인식 시스템)

  • Kim, Na-Yeon;Shin, Yun-Hee;Kim, Soo-Jeong;Kim, Jee-In;Jeong, Karp-Joo;Koo, Hyun-Jin;Kim, Eun-Yi
    • Journal of KIISE:Software and Applications
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    • v.34 no.9
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    • pp.869-879
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    • 2007
  • This paper proposes a neural network based approach for automatic human emotion recognition in textile images. To investigate the correlation between the emotion and the pattern, the survey is conducted on 20 peoples, which shows that a emotion is deeply affected by a pattern. Accordingly, a neural network based classifier is used for recognizing the pattern included in textiles. In our system, two schemes are used for describing the pattern; raw-pixel data extraction scheme using auto-regressive method (RDES) and wavelet transformed data extraction scheme (WTDES). To assess the validity of the proposed method, it was applied to recognize the human emotions in 100 textiles, and the results shows that using WTDES guarantees better performance than using RDES. The former produced the accuracy of 71%, while the latter produced the accuracy of 90%. Although there are some differences according to the data extraction scheme, the proposed method shows the accuracy of 80% on average. This result confirmed that our system has the potential to be applied for various application such as textile industry and e-business.

Korean Customer Attitudes Towards SNS Shopping

  • Cho, Young-Sang;Heo, Jeong-Yoon;Youn, Myoung-Kil
    • Journal of Distribution Science
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    • v.10 no.8
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    • pp.7-14
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    • 2012
  • As a new format of retailing, social shopping on SNS has rapidly grown in recent. Although there is much literature associated with customer behaviours in the academic world, little attention has been paid to identifying the shopping patterns of SNS shoppers. This paper will, thus, identify how perceived value has an impact on the buying intention of SNS shoppers, after illustrating what kind of factor influences the formation process of perceived value in the Korean marketplace. Given that SNS shoppers are for the most part 20s as well as 30s, the authors handed out questionnaires to them. Furthermore, based on literature review results, the conceptualised research model was developed. Despite lack of literature, the authors developed five constructs like price reduction, quantity- and time-limited message, product ranges, information-sharing, and required number of shoppers. The researchers made a considerable effort to identify the relationship between research concepts and each variable, based on a few research analysis methods such as frequency analysis, the Varimax rotation technique used orthogonal rotation, Cronbach's Alpha, PCA (Principle Component Analysis), and the like. Amongst the 5 variables used to measure the degree of influences on the perceived value as a social shopping characteristic, it has been evident that price cut, required minimum shoppers, product variety, and information-sharing have a positive impact on the perceived value formation processes of SNS customers. Also, this research implies that SNS retailers can differentiate themselves from other retailers by differently using the above factors. From a practitioner's point of view, these factors should be strategically used to increase the social shopping opportunities of SNS users. It is, furthermore, evident that the perceived value formed by the above 4 factors have played an important role in the buying decision process of SNS customers. In a sense, whether customers are aware of higher price cut rates, information-sharing, required minimum shoppers, and product variety has a positive impact on making buying decisions. From a retailer's point of view, online shopping mall operators are able to use blog as well as twitter to improve the buying intention as a marketing tool of social network, because the business activities provided by social shopping retailers, like the rapid, accurate responses to customer requirements, the provision of a variety of information, and the communications between customers are closely related to buying intentions. There are a few research limitations to conduct this empirical research. It was not easy to review prior papers, due to its lack. In spite of the increasing number of SNS shoppers in Korea, little research attention has been paid to this kind of research topic by academicians, because buying products or services through SNS is in its infancy. With regard to research populations, it would be difficult to generalise the research findings in Korea, owing to unbalanced respondent distribution. Considering the above research limitations as well as the growth of social shopping, many authors should pay considerable attention to SNS-related issues in the future, and develop the more sophisticated criteria to measure the characteristics of SNS shoppers.

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Nonlinear Time Series Prediction Modeling by Weighted Average Defuzzification Based on NEWFM (NEWFM 기반 가중평균 역퍼지화에 의한 비선형 시계열 예측 모델링)

  • Chai, Soo-Han;Lim, Joon-Shik
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.4
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    • pp.563-568
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    • 2007
  • This paper presents a methodology for predicting nonlinear time series based on the neural network with weighted fuzzy membership functions (NEWFM). The degree of classification intensity is obtained by bounded sum of weighted fuzzy membership functions extracted by NEWFM, then weighted average defuzzification is used for predicting nonlinear time series. The experimental results demonstrate that NEWFM has the classification capability of 92.22% against the target class of GDP. The time series created by NEWFM model has a relatively close approximation to the GDP which is a typical business cycle indicator, and has been proved to be a useful indicator which has the turning point forecasting capability of average 12 months in the peak point and average 6 months in the trough point during 5th to 8th cyclical period. In addition, NEWFM measures the efficiency of the economic indexes by the feature selection and enables the users to forecast with reduced numbers of 7 among 10 leading indexes while improving the classification rate from 90% to 92.22%.

Strategies for the Development of Watermelon Industry Using Unstructured Big Data Analysis

  • LEE, Seung-In;SON, Chansoo;SHIM, Joonyong;LEE, Hyerim;LEE, Hye-Jin;CHO, Yongbeen
    • The Journal of Industrial Distribution & Business
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    • v.12 no.1
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    • pp.47-62
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    • 2021
  • Purpose: Our purpose in this study was to examine the strategies for the development of watermelon industry using unstructured big data analysis. That is, this study was to look the change of issues and consumer's perception about watermelon using big data and social network analysis and to investigate ways to strengthen the competitiveness of watermelon industry based on that. Methodology: For this purpose, the data was collected from Naver (blog, news) and Daum (blog, news) by TEXTOM 4.5 and the analysis period was set from 2015 to 2016 and from 2017-2018 and from 2019-2020 in order to understand change of issues and consumer's perception about watermelon or watermelon industry. For the data analysis, TEXTOM 4.5 was used to conduct key word frequency analysis, word cloud analysis and extraction of metrics data. UCINET 6.0 and NetDraw function of UCINET 6.0 were utilized to find the connection structure of words and to visualize the network relations, and to make a cluster of words. Results: The keywords related to the watermelon extracted such as 'the stalk end of a watermelon', 'E-mart', 'Haman', 'Gochang', and 'Lotte Mart' (news: 015-2016), 'apple watermelon', 'Haman', 'E-mart', 'Gochang', and' Mudeungsan watermelon' (news: 2017-2018), 'E-mart', 'apple watermelon', 'household', 'chobok', and 'donation' (news: 2019-2020), 'watermelon salad', 'taste', 'the heat', 'baby', and 'effect' (blog: 2015-2016), 'taste', 'watermelon juice', 'method', 'watermelon salad', and 'baby' (blog: 2017-2018), 'taste', 'effect', 'watermelon juice', 'method', and 'apple watermelon' (blog: 2019-2020) and the results from frequency and TF-IDF analysis presented. And in CONCOR analysis, appeared as four types, respectively. Conclusions: Based on the results, the authors discussed the strategies and policies for boosting the watermelon industry and limitations of this study and future research directions. The results of this study will help prioritize strategies and policies for boosting the consumption of the watermelon and contribute to improving the competitiveness of watermelon industry in Korea. Also, it is expected that this study will be used as a very important basis for agricultural big data studies to be conducted in the future and this study will offer watermelon producers and policy-makers practical points helpful in crafting tailor-made marketing strategies.