• Journal of Information Science Theory and Practice
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• v.8 no.1
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• pp.56-67
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• 2020

Over the years, cultural mapping methods have been used in several applications and contexts, for diverse cultural assets and to create new conditions for the development of local and regional resources. These methods were inspired by the development of big urban centres and regions, which have been the great engine of cultural mapping growth. The main objectives of the present paper are to provide a literature review on cultural mapping methodologies and to develop exploratory research on crowdsource tools on creative tourism which were applied to one Portuguese municipality in 2017. The research was supported by the implementation and integration of geographic information systems (GIS) and web mapping, which will become part of the solution for the growth of less developed territories and to make more interactive tourist activities. Web mapping's contribution to enhance crowd participation was measured via analysis of 12 digital photos shared through crowdsourcing. The originality of this research lies in the attempt to develop a new model for creative tourism, trying to extend the implementation of Web Mapping crowdsourcing to deprived low density territories. Results show how public participation can be amplified for the tourism market by crowdsourcing tools. These tools look very promising since they can help several members of the public at different ages to contribute to territorial knowledge, engage in activities, and collaborate through digital tools. It is a step to fulfil the lack of studies in this subject and it contributes to the way we think about future studies.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.312-318
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• 2021

Lack of knowledge and digital skills is a threat to the information security of the state and society, so the formation and development of organizational culture of information security is extremely important to manage this threat. The purpose of the article is to assess the state of information security of the state and society. The research methodology is based on a quantitative statistical analysis of the information security culture according to the EU-27 2019. The theoretical basis of the study is the theory of defense motivation (PMT), which involves predicting the individual negative consequences of certain events and the desire to minimize them, which determines the motive for protection. The results show the passive behavior of EU citizens in ensuring information security, which is confirmed by the low level of participation in trainings for the development of digital skills and mastery of basic or above basic overall digital skills 56% of the EU population with a deviation of 16%. High risks to information security in the context of damage to information assets, including software and databases, have been identified. Passive behavior of the population also involves the use of standard identification procedures when using the Internet (login, password, SMS). At the same time, 69% of EU citizens are aware of methods of tracking Internet activity and access control capabilities (denial of permission to use personal data, access to geographical location, profile or content on social networking sites or shared online storage, site security checks). Phishing and illegal acquisition of personal data are the biggest threats to EU citizens. It have been identified problems related to information security: restrictions on the purchase of products, Internet banking, provision of personal information, communication, etc. The practical value of this research is the possibility of applying the results in the development of programs of education, training and public awareness of security issues.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.2
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• pp.225-238
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• 2012

Among the various security threats in online games, the use of game bots is the most serious problem. In this paper, we propose a framework for user behavior analysis for bot detection in online games. Specifically, we focus on party play that reflects the social activities of gamers: In a Massively Multi-user Online Role Playing Game (MMORPG), party play log includes a distinguished information that can classify game users under normal-user and abnormal-user. That is because the bot users' main activities target on the acquisition of cyber assets. Through a statistical analysis of user behaviors in game activity logs, we establish the threshold levels of the activities that allow us to identify game bots. Also, we build a knowledge base of detection rules based on this statistical analysis. We apply these rule reasoner to the sixth most popular online game in the world. As a result, we can detect game bot users with a high accuracy rate of 95.92%.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.21-30
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• 2021

Economic transformations have led to an increase in the role of creative assets and their central role in public life. Changes in creative activity have led to a change in the organization of the work of institutes engaged in the training of specialists, in particular teachers of labor education. Methods and approaches to training determine the development of creative industries, being the basis for models of professional training of future teachers of labor training. The purpose of an article was to develop a modern model of professional training of future teachers of labor training based on the concept of creative economy. The methodology is based on the concepts of holistic craft and creative economy. Based on the integration of pedagogical learning models "Craft as design and problem-solving", "Craft as skill and knowledge building", "Craft as product-making" and "Craft as self-expression" developed and experimentally confirmed the conceptual model of professional training of future teachers of labor training. The proposed model forms a practitioner with professional, technical, digital and creative skills who is able to transfer the experience to students. The training course "Creativity and creative thinking" has been developed. The model provided for the development of a course based on the strategy of developing professional creativity, flexibility, improvisation, openness, student activity, joint practice, student-oriented approach. The practical value implies the adaptation of the developed model of professional training of future teachers of labor education during the training of teachers in higher education, which is confirmed in the experiment.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.113-122
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• 2023

This study was conducted on the premise of the development of cultural products using relic assets of traditional culture in a knowledge and information society led by culture and soft power. It was conducted in the context of exploring the possibility of cultural content products of Wa-Dang relics excavated from traditional architecture in the Unified Silla Period and expanding the scalability of commercialization motifs that are highly useful in jewelry design. First, the original form, material, use, size, meaning, and formative aesthetics of Wa-Dang were identified through literature and media research. Among the considered Wa-Dang, 10 types of Wa-Dang which represent the category and have values in modules and patterns were selected, and, then, circular images were extracted and modularized with a "formal simplification technique." Based on the "mathematical symmetry analysis technique," which is a method of systematizing pattern composition arrangement format. we derived a planar formative element that can be used in the development of the cultural content industry and jewelry design. In order to expand its usability in the jewelry industry in the future, it was presented as a 2D digital image. In the future, we hope more studies on the various cultural content industry utilizing the traditional culture will be carried out.

• The Journal of Industrial Distribution & Business
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• v.11 no.7
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• pp.29-40
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• 2020

Purpose: In modern society, many urban problems are occurring, such as aging, hollowing out old city centers and polarization within cities. In this study, we intend to apply big data and machine learning methodologies to predict depression symptoms in the elderly population early on, thus contributing to solving the problem of elderly depression. Research design, data and methodology: Machine learning techniques used random forest and analyzed the correlation between CES-D10 and other variables, which are widely used worldwide, to estimate important variables. Dependent variables were set up as two variables that distinguish normal/depression from moderate/severe depression, and a total of 106 independent variables were included, including subjective health conditions, cognitive abilities, and daily life quality surveys, as well as the objective characteristics of the elderly as well as the subjective health, health, employment, household background, income, consumption, assets, subjective expectations, and quality of life surveys. Results: Studies have shown that satisfaction with residential areas and quality of life and cognitive ability scores have important effects in classifying elderly depression, satisfaction with living quality and economic conditions, and number of outpatient care in living areas and clinics have been important variables. In addition, the results of a random forest performance evaluation, the accuracy of classification model that classify whether elderly depression or not was 86.3%, the sensitivity 79.5%, and the specificity 93.3%. And the accuracy of classification model the degree of elderly depression was 86.1%, sensitivity 93.9% and specificity 74.7%. Conclusions: In this study, the important variables of the estimated predictive model were identified using the random forest technique and the study was conducted with a focus on the predictive performance itself. Although there are limitations in research, such as the lack of clear criteria for the classification of depression levels and the failure to reflect variables other than KLoSA data, it is expected that if additional variables are secured in the future and high-performance predictive models are estimated and utilized through various machine learning techniques, it will be able to consider ways to improve the quality of life of senior citizens through early detection of depression and thus help them make public policy decisions.

• The Journal of Society for e-Business Studies
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• v.17 no.3
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• pp.73-84
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• 2012

With transition to Knowledge society and introduction of information industry, there are many companies which have higher stock price than the suggested value from its financial information. To explain similar cases in capital markets, many researchers focus on non-financial information such as Web Traffic data or intangible assets such as intellectual property rights rather than traditional financial analysis. Besides, the relationships between financial and non-financial information with firm value are changed according to industry lifecycle. As Industry grows, financial information of company is more important for firm valuation in Capital market. We'd like to review the changes of relationships between financial information and firm valuation in Capital market especially for "Software", "Digital Contents", and "Internet" companies listed in Kosdaq market during 2000~2011. The result of data analysis shows the financial information gets more important after 2007. Inversely, it provides analytical bases that related industry gets mature. Also we show that intangible properties are more relevant to stock price of those technical based companies than others.

• Knowledge Management Research
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• v.21 no.3
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• pp.141-160
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• 2020

This study provides a new perspective on the effect of social media marketing activities (SMMA) on purchase intention in Korean cosmetic firms. The increasing use of social media has changed how firms engage their brand with consumers. This phenomenon triggered a need for this research to examine further the influence of SMMA on social brand engagement (SBE), brand equity (BE), and purchase intention (PI). The purpose of this paper is to investigate the effect of SMMA on purchase intention in Korean cosmetic firms with brand equity and social brand engagement. The factors of SMMA were identified based on previous literature reviews that have an impact on social media marketing activity. To empirically test the effects of SMMA, this study conducted a questionnaire survey on 219 social media users for data analysis out of the initial 332 survey data. The results reveal that all five SMMA elements are positively related to BE, SBE, and PI. The study enables cosmetic brands to forecast the future purchasing behavior of their customers more accurately and brings clarity to manage their assets and marketing activities as well.

• Journal of Technology Innovation
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• v.20 no.1
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• pp.115-140
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• 2012

From a point of knowledge based view, IUI(Industry-University-Institute) R&D collaboration is recognized as an important way to acquire lacking technology and knowledge. In this study, we investigated firm performance of IUI R&D collaboration on national R&D project. That is, we identified whether a collaborative research really affects firm performance, and whether firm performance is differed by types of collaboration. To test our hypotheses, we selected 250 Korean SMEs(Small and Medium Enterprises) which were funded from government R&D for 2006-2009, and we verified relations between the ratio and/or types of R&D collaboration and firm performance. Firm performance was measured by number of patent applied and ROA(Return on Assets) after completion of the project (in year t+1). Findings showed that the relationship between the ratio of R&D collaboration and technological performance was inverted U-shape. Among types of R&D collaboration, though inter-industry collaborative research was negatively related to technological performance, IUI collaborative research was positively related to technological performance. However, the ratio and types of R&D collaboration had no relation to economic performance. The results of this study will contribute to the strategy of SMEs as well as the policy of a government with regard to IUI R&D collaboration.

• Korean small business review
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• v.43 no.1
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• pp.51-83
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• 2021

This study empirically examined how the technology innovation competence of the 4th Industrial Revolution Enterprises affects management performance. It also analyzed whether there would be any difference in business performance between the 4th Industrial Revolution Enterprises and the non-4th Industrial Revolution Enterprises. The samples for analysis were analyzed using in-situ data of 2,543 enterprises classified as technical innovation enterprises and the 4th Industrial Revolution Enterprises through Korea Technology Finance Corporation's in-house technical evaluation. Variables for technology innovation competence were analyzed using variables such as the size of manpower of research and development, the level of research and development organizations, the number of intellectual property rights, the ratio of intangible assets, the amount of knowledge properties, the amount of research and development investment, and the intensiveness degree of research and development. In terms of the impact of the 4th Industrial Revolution Enterprises' technology innovation competence on business performance, all factors except for the level of research and development organizations were found to affect business performance, which supported the study hypothesis. In particular, it was confirmed that the amount of knowledge properties has had a relatively greater impact on business performance. In addition, the average comparative analysis between the 4th Industrial Revolution Enterprises and the non-4th Industrial Revolution Enterprises confirmed that the 4th Industrial Revolution Enterprises conducted higher values in the business performance.