• Journal of Korean Home Economics Education Association
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• v.31 no.4
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• pp.149-161
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• 2019

At present, we are at the point of change of the 4th industrial revolution era due to the development of artificial intelligence(AI) and rapid technological innovation that no one can predict until now. This study started from the question of 'What role should home economics education play in the era of the Fourth Industrial Revolution?'. The Fourth Industrial Revolution is characterized by AI, cloud computing, Internet of Things(IoT), big data, and Online to Offline(O2O). It will drastically change the social system, science and technology and the structure of the profession. Since the dehumanization of robots and artificial intelligence may occur, the 4th Industrial Revolution Education should be sought to foster future human resources with humanity and citizenship for the future community. In addition, the implication of education in the fourth industrial revolution, which will bring about a change to a super-intelligent and hyper-connected society, is that the role of education should be emphasized so that humans internalize their values as human beings. Character education should be established as a generalized and internalized consciousness with a concept established in the integration of the curriculum, and concrete practical strategies should be prepared. In conclusion, home economics education in the 4th industrial revolution era should play a leading role in the central role of character education, and intrinsic improvement of various human lives. The fourth industrial revolution will change not only what we do, or human mental and physical activities, but also who we are, or human identity. In the information society and digital society, it is important how quickly and accurately it is possible to acquire scattered knowledge. In the information society, it is required to learn how to use knowledge for human beings in rapid change. As such, the fourth industrial revolution seeks to lead the family, organization, and community positively by influencing the systems that shape our lives. Home economics education should take the lead in this role.

• 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.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.97-121
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• 2013

With the growing importance of knowledge for sustainable competitive advantages and innovation in a volatile environment, many researches on knowledge sharing have been conducted. However, previous researches have mostly relied on the questionnaire survey which has inherent perceptive errors of respondents. The current research has drawn the relationship among primary participant behaviors towards the participation level in knowledge sharing, basically from online user behaviors on Wikipedia, a representative community for online knowledge collaboration. Without users' participation in knowledge sharing, knowledge collaboration for creating knowledge cannot be successful. By the way, the editing patterns of Wikipedia users are diverse, resulting in different revisiting periods for the same number of edits, and thus varying results of shared knowledge. Therefore, we illuminated the participation level of knowledge sharing from two different angles of number of edits and revisiting period. The behavioral dimensions affecting the level of participation in knowledge sharing includes the article talk for public discussion and user talk for private messaging, and community registration, which are observable on Wiki platform. Public discussion is being progressed on article talk pages arranged for exchanging ideas about each article topic. An article talk page is often divided into several sections which mainly address specific type of issues raised during the article development procedure. From the diverse opinions about the relatively trivial things such as what text, link, or images should be added or removed and how they should be restructured to the profound professional insights are shared, negotiated, and improved over the course of discussion. Wikipedia also provides personal user talk pages as a private messaging tool. On these pages, diverse personal messages such as casual greetings, stories about activities on Wikipedia, and ordinary affairs of life are exchanged. If anyone wants to communicate with another person, he or she visits the person's user talk page and leaves a message. Wikipedia articles are assessed according to seven quality grades, of which the featured article level is the highest. The dataset includes participants' behavioral data related with 2,978 articles, which have reached the featured article level, with editing histories of articles, their article talk histories, and user talk histories extracted from user talk pages for each article. The time period for analysis is from the initiation of articles until their promotion to the featured article level. The number of edits represents the total number of participation in the editing of an article, and the revisiting period is the time difference between the first and last edits. At first, the participation levels of each user category classified according to behavioral dimensions have been analyzed and compared. And then, robust regressions have been conducted on the relationships among independent variables reflecting the degree of behavioral characteristics and the dependent variable representing the participation level. Especially, through adopting a motivational theory adequate for online environment in setting up research hypotheses, this work suggests a theoretical framework for the participation level of online knowledge sharing. Consequently, this work reached the following practical behavioral results besides some theoretical implications. First, both public discussion and private messaging positively affect the participation level in knowledge sharing. Second, public discussion exerts greater influence than private messaging on the participation level. Third, a synergy effect of public discussion and private messaging on the number of edits was found, whereas a pretty weak negative interaction effect of them on the revisiting period was observed. Fourth, community registration has a significant impact on the revisiting period, whereas being insignificant on the number of edits. Fifth, when it comes to the relation generated from private messaging, the frequency or depth of relation is shown to be more critical than the scope of relation for the participation level.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.45-67
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• 2016

Given the recent development of smart devices, users are producing, sharing, and acquiring a variety of information via the Internet and social network services (SNSs). Because users tend to use multiple media simultaneously according to their goals and preferences, domestic SNS users use around 2.09 media concurrently on average. Since the information provided by such media is usually textually represented, recent studies have been actively conducting textual analysis in order to understand users more deeply. Earlier studies using textual analysis focused on analyzing a document's contents without substantive consideration of the diverse characteristics of the source medium. However, current studies argue that analytical and interpretive approaches should be applied differently according to the characteristics of a document's source. Documents can be classified into the following types: informative documents for delivering information, expressive documents for expressing emotions and aesthetics, operational documents for inducing the recipient's behavior, and audiovisual media documents for supplementing the above three functions through images and music. Further, documents can be classified according to their contents, which comprise facts, concepts, procedures, principles, rules, stories, opinions, and descriptions. Documents have unique characteristics according to the source media by which they are distributed. In terms of newspapers, only highly trained people tend to write articles for public dissemination. In contrast, with SNSs, various types of users can freely write any message and such messages are distributed in an unpredictable way. Again, in the case of newspapers, each article exists independently and does not tend to have any relation to other articles. However, messages (original tweets) on Twitter, for example, are highly organized and regularly duplicated and repeated through replies and retweets. There have been many studies focusing on the different characteristics between newspapers and SNSs. However, it is difficult to find a study that focuses on the difference between the two media from the perspective of supply and demand. We can regard the articles of newspapers as a kind of information supply, whereas messages on various SNSs represent a demand for information. By investigating traditional newspapers and SNSs from the perspective of supply and demand of information, we can explore and explain the information dilemma more clearly. For example, there may be superfluous issues that are heavily reported in newspaper articles despite the fact that users seldom have much interest in these issues. Such overproduced information is not only a waste of media resources but also makes it difficult to find valuable, in-demand information. Further, some issues that are covered by only a few newspapers may be of high interest to SNS users. To alleviate the deleterious effects of information asymmetries, it is necessary to analyze the supply and demand of each information source and, accordingly, provide information flexibly. Such an approach would allow the value of information to be explored and approximated on the basis of the supply-demand balance. Conceptually, this is very similar to the price of goods or services being determined by the supply-demand relationship. Adopting this concept, media companies could focus on the production of highly in-demand issues that are in short supply. In this study, we selected Internet news sites and Twitter as representative media for investigating information supply and demand, respectively. We present the notion of News Value Index (NVI), which evaluates the value of news information in terms of the magnitude of Twitter messages associated with it. In addition, we visualize the change of information value over time using the NVI. We conducted an analysis using 387,014 news articles and 31,674,795 Twitter messages. The analysis results revealed interesting patterns: most issues show lower NVI than average of the whole issue, whereas a few issues show steadily higher NVI than the average.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.157-176
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• 2016

For a long time, mobile phone had a sole function of communication. Recently however, abrupt innovations in technology allowed extension of the sphere in mobile phone activities. Development of technology enabled realization of almost computer-like environment even on a very small device. Such advancement yielded several forms of new high-tech devices such as smartphone and tablet PC, which quickly proliferated. Simultaneously with the diffusion of the mobile devices, mobile applications for those devices also prospered and soon became deeply penetrated in consumers' daily lives. Numerous mobile applications have been released in app stores yielding trillions of cumulative downloads. However, a big majority of the applications are disregarded from consumers. Even after the applications are purchased, they do not survive long in consumers' mobile devices and are soon abandoned. Nevertheless, it is imperative for both app developers and app-store operators to understand consumer behaviors and to develop marketing strategies aiming to make sustainable business by first increasing sales of mobile applications and by also designing surviving strategy for applications. Therefore, this research analyzes consumers' mobile application usage behavior in a frame of substitution/supplementary of application categories and several explanatory variables. Considering that consumers of mobile devices use multiple apps simultaneously, this research adopts multivariate probit models to explain mobile application usage behavior and to derive correlation between categories of applications for observing substitution/supplementary of application use. The research adopts several explanatory variables including sociodemographic data, user experiences of purchased applications that reflect future purchasing behavior of paid applications as well as consumer attitudes toward marketing efforts, variables representing consumer attitudes toward rating of the app and those representing consumer attitudes toward app-store promotion efforts (i.e., top developer badge and editor's choice badge). Results of this study can be explained in hedonic and utilitarian framework. Consumers who use hedonic applications, such as those of game and entertainment-related, are of young age with low education level. However, consumers who are old and have received higher education level prefer utilitarian application category such as life, information etc. There are disputable arguments over whether the users of SNS are hedonic or utilitarian. In our results, consumers who are younger and those with higher education level prefer using SNS category applications, which is in a middle of utilitarian and hedonic results. Also, applications that are directly related to tangible assets, such as banking, stock and mobile shopping, are only negatively related to experience of purchasing of paid app, meaning that consumers who put weights on tangible assets do not prefer buying paid application. Regarding categories, most correlations among categories are significantly positive. This is because someone who spend more time on mobile devices tends to use more applications. Game and entertainment category shows significant and positive correlation; however, there exists significantly negative correlation between game and information, as well as game and e-commerce categories of applications. Meanwhile, categories of game and SNS as well as game and finance have shown no significant correlations. This result clearly shows that mobile application usage behavior is quite clearly distinguishable - that the purpose of using mobile devices are polarized into utilitarian and hedonic purpose. This research proves several arguments that can only be explained by second-hand real data, not by survey data, and offers behavioral explanations of mobile application usage in consumers' perspectives. This research also shows substitution/supplementary patterns of consumer application usage, which then explain consumers' mobile application usage behaviors. However, this research has limitations in some points. Classification of categories itself is disputable, for classification is diverged among several studies. Therefore, there is a possibility of change in results depending on the classification. Lastly, although the data are collected in an individual application level, we reduce its observation into an individual level. Further research will be done to resolve these limitations.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.1
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• pp.39-48
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• 2010

Recreation forests are in the spotlight as the place for personality development, mind and body comfort, companionship, and environment education in forests and valleys. Visitors to recreation forests have been on the increase along with booming in recreation forest building since 1988. Recreation forests are being categorized according to some features such as regional and environmental condition. Recreation forests, however, have not met the expectations of some visitors who want to take a rest with calmness due to the influence of the 5-day-work-week system, increasing interest in rest, leisure, and well-being, and users converge during weekends, summer, and the tourist season. In order to improve visitors' satisfaction efficiently, this study surveyed the level of satisfaction in each cluster based on the precedent study which had classified 85 national or public recreation forests in Korea into clusters. Questionnaires were distributed properly to each cluster and, of the 1,132 questionnaires collected, 1,015 were valid and used for analysis. Reliability of questionnaires and statistical validity of the model were verified. As a result, there are meaningful differences in the ranking of independent variables which affect the level of satisfaction according to clusters. Variables in rest and fatigue recovery have the strongest influence on the level of satisfaction in the clusters of potential factor, internal activation factor, and mixed potential capacity factor. In the use performance and visiting condition factor cluster, appropriateness of visit cost is most influential and, in the education cluster, connectivity with tourist attractions around it is most affective. These results can provide priority in services and maintenance of recreation forests for improving the level of satisfaction and differentiate the distribution of resources according to clusters.

• Korean Journal of Agricultural Science
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• v.14 no.1
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• pp.164-185
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• 1987

The Korean economy has been developed rapidly in the course of implementing the five year economic development plans since 1962. Accordingly the industrial and employment structure have been changed from the traditional agriculture to modem industrial economy. In the course of implementing export oriented industrialization policies, rural farm economy has been encountered labour shortage owing to rural farm population drain to urban areas, rural wage hike and pressure on farm operation costs, and possibility of farm productivity decrease. To cope with the above problems the Korean government has supplied farm machinery such as power tillers, tractors, transplanters, binders, combines, dryers and etc. by means of the favorable credit support and subsidies. The main objectives of this study are to identify the investment effects of farm mechanization such as B/C and Internal Rate of Return by machinery and operation patterns, changes of labour requirement per 10a for rice culture since 1965, partial farm budget of rice with and without mechanization, and estimation labour input with full mechanization. To achieve the objectives Saemaeul farm mechanization groups, common ownership and operation, and farms with private ownership and operation were surveyed mainly in Nonsan granary area, Chungnam province. The results of this study are as follows 1. The national average of labor input per 10a of paddy has decreased from 150.1Hr in 1965 to 87.2Hr in 1985 which showes 42% decrease of labour inputs. On the other hand the hours of labour input in Nonsan area have also decreased from 150.1Hr to 92.8Hr, 38% of that in 1965, during the same periods. 2. The possible labor saving hours per 10a of Paddy was estimated at 60 hours by substituting machine power for labor forces in the works of plowing, puddling, transplanting, harvesting and threshing, transporting and drying The labor savings were derived from 92.8 hours in 1986 deducting 30 hours of labor input with full mechanization in Nonsan area. 3. Social benefits of farm mechanization were estimated at 124,734won/10a including increment of rice (10%): 34,064won,labour saving: 65,800won,savings of conventional farm implements: 18,000 won and savings of animal power: 6,870won. 4. Rental charges by works prevailing in the area were 12,000won for land preparation, 15,000won for transplanting with seedlings, 19,500won for combine works and 6,000won for drying paddy. 5. Farm income per 10a of paddy with and without mechanization were amounted to 247,278won and 224,768won respectively. 6. Social rate of return of the machinery were estimated at more than 50% in all operation patterns. On the other hand internal rate of return of the machinery except tractors were also more than 50% but IRR of tractors by operation patterns were equivalent to 0 to 9%. From the view point of farmers financial status, private owner-operation of tractors is considered uneconomical. Tractor operation by Saemaeul mechanization groups would be economical considering the government subsidy, 40% of tractor price. 7. Farmers recommendations for the government that gained through field operation of farm machinery are to train maintenance technology for rural youth, to standardize the necessary parts of machinery, to implement price tag system, to intercede spare parts and provide marketing information to farmers by rural institutions as RDA,NACF,GUN office and FLIA.

• Progress in Medical Physics
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• v.25 no.4
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• pp.233-241
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• 2014

The aim of this study is to develop a new software tool for 3D dose verification using $PRESAGE^{REU}$ Gel dosimeter. The tool included following functions: importing 3D doses from treatment planning systems (TPS), importing 3D optical density (OD), converting ODs to doses, 3D registration between two volumetric data by translational and rotational transformations, and evaluation with 3D gamma index. To acquire correlation between ODs and doses, CT images of a $PRESAGE^{REU}$ Gel with cylindrical shape was acquired, and a volumetric modulated arc therapy (VMAT) plan was designed to give radiation doses from 1 Gy to 6 Gy to six disk-shaped virtual targets along z-axis. After the VMAT plan was delivered to the targets, 3D OD data were reconstructed from 512 projection data from $Vista^{TM}$ optical CT scanner (Modus Medical Devices Inc, Canada) per every 2 hours after irradiation. A curve for converting ODs to doses was derived by comparing TPS dose profile to OD profile along z-axis, and the 3D OD data were converted to the absorbed doses using the curve. Supra-linearity was observed between doses and ODs, and the ODs were decayed about 60% per 24 hours depending on their magnitudes. Measured doses from the $PRESAGE^{REU}$ Gel were well agreed with the TPS doses at central region, but large under-doses were observed at peripheral region at the cylindrical geometry. Gamma passing rate for 3D doses was 70.36% under the gamma criteria of 3% of dose difference and 3 mm of distance to agreement. The low passing rate was resulted from the mismatching of the refractive index between the PRESAGE gel and oil bath in the optical CT scanner. In conclusion, the developed software was useful for 3D dose verification from PRESAGE gel dosimetry, but further improvement of the Gel dosimetry system were required.

• Progress in Medical Physics
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• v.25 no.4
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• pp.298-303
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• 2014

In this study, we examine the trends and types of incidents frequently occur during radiation therapy by using the data from the radiation oncology safety information system (ROSIS), according to discovery method explores the development direction of future research accident cause factor control method. This study was carried out analysis of incident data in ROSIS nearly 1163 cases in last 11 years from 2003 to 2013. We categorized into treatment methods, found the time, discoverer of occupations and finding ways to analyze the data. Then, we calculate the percentage and the classification for each item. About 1163 cases of incident cases including the near miss cases, external radiation therapy, brachytherapy and other were 97%, 2% and 1%. In the case was improperly planned dose delivery was 44% (497 cases) which 429 cases (86%) was found before 3 fractions and 13 cases were found after 11 fractions. The investigation was found to be distributed in various a found times. Approximately 42% of found time was during treatment and 29% of patients were found the problem during inspection chart. Occupation to discover the most radiation accidents was the radiation therapist (53%) who works in treatment room. Among 1163 incidence cases, 24% cases were found the accident before the treatment, therefore most of accident were found after of during the treatment (70%, 813 cases). This trend is acquired through ROSIS analysis, is expected to be not significantly different in the case of Korea, so it is necessary more diverse and systematic research for the prevention and early detection by using the ROSIS data.

• Geophysics and Geophysical Exploration
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• v.11 no.2
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• pp.99-108
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• 2008

To extend our detailed knowledge for the Hwasan caldera, we carried out magnetotelluric (MT) survey, which is pretty sensitive to electrical property variation in both horizontal and vertical direction of subsurface, across the Hwasan caldera with the direction of EW. The 2-D inversion results of observed MT data lead to following conclusions. Firstly, the depth of the basin basement inferred by the MT inversion results matches well with that suggested by previous potential studies, but the basement resistivity seems fairly low when compared to that of general case. This feature might be related with the large-scaled, highly conductive layer beneath the Euisung Sub-basin suggested by the previous MT study. Secondly, the high resistivity zones reaching to 4000 $\Omega{\cdot}m$ are imaged around two external ring fault boundaries. These zones are thought of as the response of the rhyolitic dykes intruding along the ring fault, and in the previous gravity data correspond to relatively high density anomalies. Thirdly, low resistivity zone reaching to 200 $\Omega{\cdot}m$ is detected around a depth of 1km beneath the central part of the caldera, which has not been yet reported in korean geophysical literatures. If we take account of the evolution model of the Hwasan caldera, this zone is regarded as the past sedimentary layer that subsided during the period of forming external ring fault system. In addition, the relatively low density anomaly observed in the central part of the caldera may be attributed to this sedimentary layer.