• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.139-148
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• 2020

Due to change in circumstances in the 2000s such as severe birthrate decline and shortened military service period, the armed forces of the Republic of Korea is currently turning to technologies and equipments from manpower, developing it to become high-tech, high-speed, and complex, resulting in an environment in which a single mistake could cause a mass mortality crisis.It is also evident that, considering aspects such as safety training curriculums and achievements of advanced countries and private education, hands-on training is a must in preventing suicides and accidents in the military, and establishing safety training centers is crucial for systematic and effective hands-on training.Soldiers who are joining the army as of now have experienced the Internet ever since they were born and easily use both virtual and augmented reality, and the current level of science and technology has developed to the point where most of the public safety experience centers are able to be replaced by virtual and augmented reality (VR/AR). Therefore, considering the aspects such as installation space, construction costs, maintenance costs, user characteristics, and education effects, other than for those trainings where real models and objects are more effective such as first aid training, it is with a strong recommendation that establishing military safety training facilities with VR/AR (Virtual and augmented reality) is a must in the coming future. We have derived the need for hands-on training by considering the development of virtual and augmented reality (VR/AR), analysis of operation status of the public safety experience centers, characteristics of military units, installation and maintenance costs, and proposed plan to establish safety training centers where effective training performance can be achieved at a lower cost than the public safety experience center. In addition, we suggested the scale of the required safety training center and the composition of the experience rooms considering the number of trainees and the environment of each military units. Given this analysis it will contribute to the prevention of military safety and suicide by building a safety training center in the future.

• Asia pacific journal of information systems
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• v.18 no.4
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• pp.105-130
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• 2008

Consumers of e-learning market differ from those of other markets in that they are replaced in a specific time scale. For example, e-learning contents aimed at highschool senior students cannot be consumed by a specific consumer over the designated period of time. Hence e-learning service providers need to attract new groups of students every year. Due to lack of information on products designed for continuously emerging consumers, the consumers face difficulties in making rational decisions in a short time period. Increased uncertainty of product purchase leads customers to herding behaviors to obtain information of the product from others and imitate them. Taking into consideration of these features of e-learning market, this study will focus on the online herding behavior in purchasing e-learning contents. There is no definite concept for e-learning. However, it is being discussed in a wide range of perspectives from educational engineering to management to e-business etc. Based upon the existing studies, we identify two main view-points regarding e-learning. The first defines e-learning as a concept that includes existing terminologies, such as CBT (Computer Based Training), WBT (Web Based Training), and IBT (Internet Based Training). In this view, e-learning utilizes IT in order to support professors and a part of or entire education systems. In the second perspective, e-learning is defined as the usage of Internet technology to deliver diverse intelligence and achievement enhancing solutions. In other words, only the educations that are done through the Internet and network can be classified as e-learning. We take the second definition of e-learning for our working definition. The main goal of this study is to investigate what factors affect consumer intention to purchase e-learning contents and to identify the differential impact of the factors between consumers with purchase experience and those without the experience. To accomplish the goal of this study, it focuses on herding behavior and perceived usefulness as antecedents to behavioral intention. The proposed research model in the study extends the Technology Acceptance Model by adding herding behavior and usability to take into account the unique characteristics of e-learning content market and e-learning systems use, respectively. The current study also includes consumer experience with e-learning content purchase because the previous experience is believed to affect purchasing intention when consumers buy experience goods or services. Previous studies on e-learning did not consider the characteristics of e-learning contents market and the differential impact of consumer experience on the relationship between the antecedents and behavioral intention, which is the target of this study. This study employs a survey method to empirically test the proposed research model. A survey questionnaire was developed and distributed to 629 informants. 528 responses were collected, which consist of potential customer group (n = 133) and experienced customer group (n = 395). The data were analyzed using PLS method, a structural equation modeling method. Overall, both herding behavior and perceived usefulness influence consumer intention to purchase e-learning contents. In detail, in the case of potential customer group, herding behavior has stronger effect on purchase intention than does perceived usefulness. However, in the case of shopping-experienced customer group, perceived usefulness has stronger effect than does herding behavior. In sum, the results of the analysis show that with regard to purchasing experience, perceived usefulness and herding behavior had differential effects upon the purchase of e-learning contents. As a follow-up analysis, the interaction effects of the number of purchase transaction and herding behavior/perceived usefulness on purchase intention were investigated. The results show that there are no interaction effects. This study contributes to the literature in a couple of ways. From a theoretical perspective, this study examined and showed evidence that the characteristics of e-learning market such as continuous renewal of consumers and thus high uncertainty and individual experiences are important factors to be considered when the purchase intention of e-learning content is studied. This study can be used as a basis for future studies on e-learning success. From a practical perspective, this study provides several important implications on what types of marketing strategies e-learning companies need to build. The bottom lines of these strategies include target group attraction, word-of-mouth management, enhancement of web site usability quality, etc. The limitations of this study are also discussed for future studies.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.161-167
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• 2010

Social individualized broadcasting increases rapidly in an environment that combines communication and broadcasting. Real-time individualized broadcasting is a service that is provided by multiple individuals to many and unspecified persons. In contrast, newly introduced individualized broadcasting service is a service that has not been experienced socially and culturally and therefore many problems are expected. The newly emerging real-time individualized broadcasting service may bring about various dysfunctions as well as desirable functions. Establishment of guideline and its implementation based in vulnerability analysis are necessary to prevent the expected dysfunctions and reinforce the desirable functions. Therefore, the purpose of this paper is to examine dysfunctions of the information-oriented society which threaten cyber-norms, cyber-morality, cyber-dangers, cyber-democracy, etc. at the level of social individualized broadcasting service and to propose appropriate guidelines. Through this paper, first, future changes of dysfunctions of the information-oriented society due to individualized broadcasting service can be forecast, and countermeasures and policy directions can be proposed. Second, Dysfunctions of ICT-based service that may emerge in individualized broadcasting service can be forecast and correct guideline can be prepared to reduce potential dangers and increase desirable functions of the service. This paper will analyze in various aspects the characteristics of a new media with the focus on individualized broadcasting service among the new ICT-integrated services, and forecast the appearance and aggravation of the dysfunctions and then draw the guideline.

• Journal of KIBIM
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• v.2 no.1
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• pp.27-39
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• 2012

Public construction projects need complex and multi-functional management skill, since the most of public construction projects are comprised of multi-project and mega-projects. In order to effectively manage construction projects, PMIS is widely used. However the majority of the current PMIS have been developed as a single project-oriented business management system. Thus compatibility problems are encountered during the process of integrating the entire systems to manage the multi-complex projects. In addition, the form of orders applying BIM are increased recently, but the research and development of BIM based PMIS are still lacking. In this study, therefore, the functions of PMIS main objectives based on the analysis of PMIS As-Is and To-Be of PMIS, the dual management system utilizing Internet and Intranet will be proposed to integrate the individual PMIS with Integrated Program Management System. Rather than combining commercial BIM tool and PMIS directly, which is the common method of failure, the sequential process model to adopt BIM based PMIS is also explained. Step-by-step development method of BIM based PMIS is suggested to prepare for the activation of BIM technology in the nearest future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.157-163
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• 2013

Data mining is a useful technology that can support new discoveries based on the pattern analysis and a variety of linkages between data, and currently is utilized in various fields such as finance, marketing, medical. In this paper, we propose an effective utilization method of data based on analysis of spatial data mining. We make use of basic data of foreigners living in Seoul. However, the data has some features distinguished from other areas of data, classification as sensitive information and legal problem such as personal information protection. So, we use the basic statistical data that does not contain personal information. The main features and contributions of the proposed method are as follows. First, we can use Big Data as information through a variety of ways and can classify and cluster Big Data through refinement. Second. we can use these kinds of information for decision-making of future and new patterns. In the performance evaluation, we will use visual approach through graph of themes. The results of performance evaluation show that the analysis using data mining technology can support new discoveries of patterns and results.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.59-71
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• 2012

PKI-based public key scheme is outstanding in terms of authenticity and privacy. Nevertheless its application brings big burden due to the certificate/key management. It is difficult to apply it to limited computing devices in WSN because of its high encryption complexity. The Bilinear Pairing emerged from the original IBE to eliminate the certificate, is a future significant cryptosystem as based on the DDH(Decisional DH) algorithm which is significant in terms of computation and secure enough for authentication, as well as secure and faster. The practical EC Weil Pairing presents that its encryption algorithm is simple and it satisfies IND/NM security constraints against CCA. The Random Oracle Model based IBE PKG is appropriate to the structure of our target system with one secret file server in the operational perspective. Our work proposes modification of the Weil Pairing as proper to the closed network for secret file distribution[2]. First we proposed the improved one computing both encryption and message/user authentication as fast as O(DES) level, in which our scheme satisfies privacy, authenticity and integrity. Secondly as using the public key ID as effective as PKI, our improved IBE variant reduces the key exposure risk.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.9-16
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• 2020

In the Image processing and computer vision, the problem of reconstructing from one image to another or generating a new image has been steadily drawing attention as hardware advances. However, the problem of computer-generated images also continues to emerge when viewed with human eyes because it is not natural. Due to the recent active research in deep learning, image generating and improvement problem using it are also actively being studied, and among them, the network called Generative Adversarial Network(GAN) is doing well in the image generating. Various models of GAN have been presented since the proposed GAN, allowing for the generation of more natural images compared to the results of research in the image generating. Among them, pix2pix is a conditional GAN model, which is a general-purpose network that shows good performance in various datasets. pix2pix is based on U-Net, but there are many networks that show better performance among U-Net based networks. Therefore, in this study, images are generated by applying various networks to U-Net of pix2pix, and the results are compared and evaluated. The images generated through each network confirm that the pix2pix model with Attention, R2, and Attention-R2 networks shows better performance than the existing pix2pix model using U-Net, and check the limitations of the most powerful network. It is suggested as a future study.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.97-107
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• 2020

This study aims to conduct a comprehensive meta-study from the perspective of content analysis to explore trends in Korean academic research on the sharing economy by using the big data analytics. Comprehensive meta-analysis methodology can examine the entire set of research results historically and wholly to illuminate the tendency or properties of the overall research trend. Academic research related to the sharing economy first appeared in the year in which Professor Lawrence Lessig introduced the concept of the sharing economy to the world in 2008, but research began in earnest in 2013. In particular, between 2006 and 2008, research improved dramatically. In order to grasp the overall flow of domestic academic research of trends, 8 years of papers from 2013 to the present have been selected as target analysis papers, focusing on titles, keywords, and abstracts using database of electronic journals. Big data analysis was performed in the order of cleaning, analysis, and visualization of the collected data to derive research trends and insights by year and type of literature. We used Python3.7 and Textom analysis tools for data preprocessing, text mining, and metrics frequency analysis for key word extraction, and N-gram chart, centrality and social network analysis and CONCOR clustering visualization based on UCINET6/NetDraw, Textom program, the keywords clustered into 8 groups were used to derive the typologies of each research trend. The outcomes of this study will provide useful theoretical insights and guideline to future studies.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.59-68
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• 2020

The present study aims to explore the influence of BTS, which is popular around the world. Specifically, it aims to look at differences between Korean and Chinese BTS female fandom. Besides, it also explores factors affecting fandom's daily happiness. The study conducted a survey with Korean and Chinese female fans. Findings from surveys suggest that first, there are differences on star attributes, fandom activity and illusory romance between Korean and Chinese female fandom. Specifically, Chinese female fandom's professionalism and artistic attractiveness which are included in star attributes, and illusory romance which is gained in fandom activity are higher than Korean. In addition, Korean female fans actively participated in offline fandom activities, while Chinese female fans actively participated in online fandom activities. Second, it is found that fandom activity, star identification and illusory romance have positive effects on daily happiness. Based on these findings, implication, limitations, and topics for future research are discussed.