• Korean Journal of Culture and Social Issue
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• v.10 no.2
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• pp.1-15
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• 2004

The drastically changing society has brought diverse types of families, and these diversities are changing the concept of the word 'family' itself. Inevitably, these changes cause different viewpoints among family members, developing into conflicts and social issues. In this paper, generational family problems, which are caused by changes within the family as a result of the variously, diversely changing society, are observed to suggest a resolution. Looking into the functional variety that today's structural change within a family demands, several positives changes described below have been observed; Firstly, the change in the way of interaction among family members; Secondly, the demand for continuance on relational functions including love, care, etc, as a psychological resource of family; Thirdly, the conversion from form's sake relationship to actual relationship; and Lastly, the usage of a clearer communications network. The interaction between the parent-children relationship, according to the changes in family life cycle, is also re-focused to seek resolutions for intergenerational conflicts. The results are as follows; Firstly, the changeability of various family types today must be accepted, and the functional aspects of changing families must be emphasized ; Secondly, the mutual-exchanging value of each generation must be accepted, strengthening relational functions between generations; Thirdly, it is necessary to refocus filial piety. In other words, though the intergenerational transmission of family functions may become the basis of lineage and clan formation, it won't be possible without interaction between generation.

• Information Systems Review
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• v.21 no.1
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• pp.23-38
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• 2019

The social network service (SNS) is one of the important marketing channels, so many companies actively exploit SNSs by posting SNS messages with appropriate content and style for their customers. In this paper, we focused on the psychological distances embedded in the SNS messages and developed a method to measure the psychological distance in SNS message by mixing a traditional content analysis, natural language processing (NLP), and machine learning. Through a traditional content analysis by human coding, the psychological distance was extracted from the SNS message, and these coding results were used for input data for NLP and machine learning. With NLP, word embedding was executed and Bag of Word was created. The Support Vector Machine, one of machine learning techniques was performed to train and test the psychological distance in SNS message. As a result, sensitivity and precision of SVM prediction were significantly low because of the extreme skewness of dataset. We improved the performance of SVM by balancing the ratio of data by upsampling technique and using data coded with the same value in first content analysis. All performance index was more than 70%, which showed that psychological distance can be measured well.

• Information Systems Review
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• v.19 no.4
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• pp.27-42
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• 2017

With the rapid development in network, graphic technology, and digital technology, content industry is emerging as an important industry for new cultural development and economic development. The development in digital content technology has remarkably expanded the generation and distribution of contents, thereby creating new value and extending into a large distribution market. However, the ease of distribution and duplication, which characterizes digital technology, has increased the circulation of illegal contents due to illegal copying, theft, and alteration. The damage caused by this illegal content is severe. Currently, a copyright protection system targeting online sites is available. By contrast, no system has been established for offline companies that sell offline genuine content, which compete with online companies. The demand for content of overseas tourists is increasing due to the Korean wave craze. Nevertheless, many offline content providers have lost competitiveness due to illegal content distribution with online companies. In this study, we analyzed the case and status of similar copyright certification systems in Korea and overseas through previous research and studied a system to certify the offline genuine contents business. In addition to the case analysis, we focused on interviews obtained through in-depth interviews with the copyright stakeholders. We also developed a certification framework by establishing the certification domain, certification direction, and incentive of the certification system for offline businesses with genuine content. Selected certification direction is ethical, open, inward, store, and rigid (post evaluation). This study aimed to increase awareness among consumers about the use of genuine content and establish a transparent trading order in a healthy content market.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.211-232
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• 2014

Recently, there is a growing interest toward social commerce using SNS(Social Networking Service), and the size of its market is also expanding due to popularization of smart phones, tablet PCs and other smart devices. Accordingly, various studies have been attempted but it is shown that most of the previous studies have been conducted from perspectives of the users. The purpose of this study is to derive user-centered CSF(Critical Success Factor) of social commerce from the previous studies and analyze the CSF perception gap between social commerce service providers and users. The CSF perception gap between two groups shows that there is a difference between ideal images the service providers hope for and the actual image the service users have on social commerce companies. This study provides effective improvement directions for social commerce companies by presenting current business problems and its solution plans. For this, This study selected Korea's representative social commerce business Ticket Monster, which is dominant in sales and staff size together with its excellent funding power through M&A by stock exchange with the US social commerce business Living Social with Amazon.com as a shareholder in August, 2011, as a target group of social commerce service provider. we have gathered questionnaires from both service providers and the users from October 22, 2012 until October 31, 2012 to conduct an empirical analysis. We surveyed 160 service providers of Ticket Monster We also surveyed 160 social commerce users who have experienced in using Ticket Monster service. Out of 320 surveys, 20 questionaries which were unfit or undependable were discarded. Consequently the remaining 300(service provider 150, user 150)were used for this empirical study. The statistics were analyzed using SPSS 12.0. Implications of the empirical analysis result of this study are as follows: First of all, There are order differences in the importance of social commerce CSF between two groups. While service providers regard Price Economic as the most important CSF influencing purchasing intention, the users regard 'Trust' as the most important CSF influencing purchasing intention. This means that the service providers have to utilize the unique strong point of social commerce which make the customers be trusted rathe than just focusing on selling product at a discounted price. It means that service Providers need to enhance effective communication skills by using SNS and play a vital role as a trusted adviser who provides curation services and explains the value of products through information filtering. Also, they need to pay attention to preventing consumer damages from deceptive and false advertising. service providers have to create the detailed reward system in case of a consumer damages caused by above problems. It can make strong ties with customers. Second, both service providers and users tend to consider that social commerce CSF influencing purchasing intention are Price Economic, Utility, Trust, and Word of Mouth Effect. Accordingly, it can be learned that users are expecting the benefit from the aspect of prices and economy when using social commerce, and service providers should be able to suggest the individualized discount benefit through diverse methods using social network service. Looking into it from the aspect of usefulness, service providers are required to get users to be cognizant of time-saving, efficiency, and convenience when they are using social commerce. Therefore, it is necessary to increase the usefulness of social commerce through the introduction of a new management strategy, such as intensification of search engine of the Website, facilitation in payment through shopping basket, and package distribution. Trust, as mentioned before, is the most important variable in consumers' mind, so it should definitely be managed for sustainable management. If the trust in social commerce should fall due to consumers' damage case due to false and puffery advertising forgeries, it could have a negative influence on the image of the social commerce industry in general. Instead of advertising with famous celebrities and using a bombastic amount of money on marketing expenses, the social commerce industry should be able to use the word of mouth effect between users by making use of the social network service, the major marketing method of initial social commerce. The word of mouth effect occurring from consumers' spontaneous self-marketer's duty performance can bring not only reduction effect in advertising cost to a service provider but it can also prepare the basis of discounted price suggestion to consumers; in this context, the word of mouth effect should be managed as the CSF of social commerce. Third, Trade safety was not derived as one of the CSF. Recently, with e-commerce like social commerce and Internet shopping increasing in a variety of methods, the importance of trade safety on the Internet also increases, but in this study result, trade safety wasn't evaluated as CSF of social commerce by both groups. This study judges that it's because both service provider groups and user group are perceiving that there is a reliable PG(Payment Gateway) which acts for e-payment of Internet transaction. Accordingly, it is understood that both two groups feel that social commerce can have a corporate identity by website and differentiation in products and services in sales, but don't feel a big difference by business in case of e-payment system. In other words, trade safety should be perceived as natural, basic universal service. Fourth, it's necessary that service providers should intensify the communication with users by making use of social network service which is the major marketing method of social commerce and should be able to use the word of mouth effect between users. The word of mouth effect occurring from consumers' spontaneous self- marketer's duty performance can bring not only reduction effect in advertising cost to a service provider but it can also prepare the basis of discounted price suggestion to consumers. in this context, it is judged that the word of mouth effect should be managed as CSF of social commerce. In this paper, the characteristics of social commerce are limited as five independent variables, however, if an additional study is proceeded with more various independent variables, more in-depth study results will be derived. In addition, this research targets social commerce service providers and the users, however, in the consideration of the fact that social commerce is a two-sided market, drawing CSF through an analysis of perception gap between social commerce service providers and its advertisement clients would be worth to be dealt with in a follow-up study.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• The Journal of Society for e-Business Studies
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• v.17 no.1
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• pp.23-38
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• 2012

Massive Multiplayer Online Role Playing Games(MMORPGs) headed by some Korean game companies such as NC Soft, NHN, and Nexon have exploded in recent years. However, it becomes one of the major challenges for the MMORPG developers to design their games to appeal to gamers since only a few MMORPGs succeed whereas they require a huge amount of initial investment. Under this background, our study derives the major elements for designing MMORPG from the literature, and identifies the ones critical to the users' satisfaction and their willingness to pay among the derived elements. Though most previous studies on the design elements of MMORPG have used analytic hierarchy process(AHP), our study adopts artificial neural network(ANN) as the tool for identifying key success factors in designing MMORPG. The results of our study show that the elements of the game contents quality have a bigger effect on the user's satisfaction, whereas the ones of the value-added systems have a bigger effect on the user's willingness to pay. They also show that user interface affects both the user's satisfaction and willingness to pay most. These results imply that the strategies for the development of MMORPG should be aligned with its goal and market penetration strategy. They also imply that the satisfaction and revenue generation from MMORPG cannot be achieved without convenient and easy control environment. It is expected that the new findings of our study would be useful forthe developers or publishers of MMORPGs to build their own business strategies.

• Journal of Science Education
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• v.39 no.3
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• pp.358-375
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• 2015

The purposes of this study were to investigate the value, necessity and legitimacy of STEAM Education and to propose practical approaching methods for STEAM Education to be applicable in Korea through a variety of literature review, case studies and collecting suggestions from domestic and international educational experts. The research questions are as follows: (1) To investigate the perception, understanding and recognitions of domestic and foreign professionals in STEAM education. (2) To analyze policy implications for an improvement in STEAM. The following aspects of STEAM were found to be challenges in our current STEAM policy after analyzing multiple questionnaires with the professionals and case studies including their experiences, understanding, supports and directions of the policy from the governments. The results indicate that (1) there was a lack of precise and conceptual understanding of STEAM in respect to experience. Training sessions for teachers in this field to help transform their perception is necessary. Development of practical programs with an easy access is also required. It is important to get the aims of related educational activities recognized by the professionals and established standards for an evaluation. The experts perceived that a theme-based learning is the most preferred and effective approaching method and the programs that develop creative thinking and learning applicable to practice are required to promote. (2) The results indicate that there was a lack of programs and inducements for supporting outstanding STEAM educators. It is shown that making an appropriate environment for STEAM education takes the first priority before training numbers of teachers unilaterally, thus securing enough budget seems critical. The professionals also emphasize on developing specialized teaching materials that include diverse inter-related subjects such as science technology, engineering, arts and humanities and social science with diverse viewpoints and advanced technology. This work requires a STEAM network for teachers to link up and share their materials, documents and experiences. It is necessary to get corporations, universities, and research centers participated in the network. (3) With respect to direction, it is necessary to propose policy that makes STEAM education ordinary and more practical in the present education system. The professionals have recommended training sessions that help develop creative thinking and amalgamative problem-solving techniques. They require reducing the workload of teachers and changing teachers' perspectives towards STEAM. They further urge a tight cooperation between departments of the government related with STEAM.

• Journal of radiological science and technology
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• v.34 no.1
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• pp.17-25
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• 2011

In this study, we examined the impact caused by chronic exposure to Mn by investigating the degree of brain activation based on the data of recognition activities using fMRI (functional magnetic resonance imaging). A questionnaire survey, blood tests, and fMRI tests were carried out with respect to two groups. Group 1 was an exposure group consisting of 15 male workers who are 34 years old or older, and who worked for longer than 10 years in a shipbuilding factory as a welder. Group 2 was a control group consisting of 15 workers in manufacturing industries with the same gender and age. The results showed that blood Mn concentration of Group 1($1.3\;{\mu}g/dl$) was significantly higher than that of Group 2($0.8\;{\mu}g/dl$)(p < 0.001), and Pallidal Index (PI) of Group 1 was also significantly higher than that of Group 2 (p < 0.001). PI value of the group whose blood Mn concentration was $0.93\;{\mu}g/dl$ or higher was significantly higher than that of the group whose blood Mn concentration was less than $0.93 \;{\mu}g/dl$ (p < 0.001). As for brain activity area within the control group, the right and the left areas of occipital cortex showed significant activity and the left area of middle temporal cortex, the right area of superior inferior frontal cortex and inferior parietal cortex showed significant activity. Unlike the control group, the exposure group showed significant activity on the right area of superior inferior temporal cortex, the left of insula area. In the comparison of brain activity areas between the two groups, the exposure group showed significantly higher activation than the control group in such areas as the right inferior temporal cortex, the left area of superior parietal cortex and occipital cortex, and cerebellum including middle temporal cortex. However, in nowhere the control group showed more activated area than the exposure group. As the final outcome, chronic exposure to Mn increased brain activity during implementation of arithmetic task. In an identical task, activation increased in superior inferior temporal cortex, and insula area. And it was discovered that brain activity increase in temporal area and occipital area was more pronounced in the exposure group than in the control group. This result suggests that chronic exposure to Mn in the work environment affects brain activation neuro-network.

• Asia pacific journal of information systems
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• v.21 no.4
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• pp.45-62
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• 2011

The notion of information systems (IS) continuance has recently emerged as one of the most important research issues in the field of IS. A great deal of research has been conducted thus far on the basis of theories adapted from various disciplines including consumer behaviors and social psychology, in addition to theories regarding information technology (IT) acceptance. This previous body of knowledge provides a robust research framework that can already account for the determination of IS continuance; however, this research points to other, thus-far-unelucidated determinant factors such as habit, which were not included in traditional IT acceptance frameworks, and also re-emphasizes the importance of emotion-related constructs such as satisfaction in addition to conscious intention with rational beliefs such as usefulness. Experiences should also be considered one of the most important factors determining the characteristics of information system (IS) continuance and the features distinct from those determining IS acceptance, because more experienced users may have more opportunities for IS use, which would allow them more frequent use than would be available to less experienced or non-experienced users. Interestingly, experience has dual features that may contradictorily influence IS use. On one hand, attitudes predicated on direct experience have been shown to predict behavior better than attitudes from indirect experience or without experience; as more information is available, direct experience may render IS use a more salient behavior, and may also make IS use more accessible via memory. Therefore, experience may serve to intensify the relationship between IS use and conscious intention with evaluations, On the other hand, experience may culminate in the formation of habits: greater experience may also imply more frequent performance of the behavior, which may lead to the formation of habits, Hence, like experience, users' activation of an IS may be more dependent on habit-that is, unconscious automatic use without deliberation regarding the IS-and less dependent on conscious intentions, Furthermore, experiences can provide basic information necessary for satisfaction with the use of a specific IS, thus spurring the formation of both conscious intentions and unconscious habits, Whereas IT adoption Is a one-time decision, IS continuance may be a series of users' decisions and evaluations based on satisfaction with IS use. Moreover. habits also cannot be formed without satisfaction, even when a behavior is carried out repeatedly. Thus, experiences also play a critical role in satisfaction, as satisfaction is the consequence of direct experiences of actual behaviors. In particular, emotional experiences such as enjoyment can become as influential on IS use as are utilitarian experiences such as usefulness; this is especially true in light of the modern increase in membership-based hedonic systems - including online games, web-based social network services (SNS), blogs, and portals-all of which attempt to provide users with self-fulfilling value. Therefore, in order to understand more clearly the role of experiences in IS continuance, analysis must be conducted under a research framework that includes intentions, habits, and satisfaction, as experience may not only have duration-based moderating effects on the relationship between both intention and habit and the activation of IS use, but may also have content-based positive effects on satisfaction. This is consistent with the basic assumptions regarding the determining factors in IS continuance as suggested by Oritz de Guinea and Markus: consciousness, emotion, and habit. The principal objective of this study was to explore and assess the effects of experiences in IS continuance, with special consideration given to conscious intentions and unconscious habits, as well as satisfaction. IN service of this goal, along with a review of the relevant literature regarding the effects of experiences and habit on continuous IS use, this study suggested a research model that represents the roles of experience: its moderating role in the relationships of IS continuance with both conscious intention and unconscious habit, and its antecedent role in the development of satisfaction. For the validation of this research model. Korean university student users of 'Cyworld', one of the most influential social network services in South Korea, were surveyed, and the data were analyzed via partial least square (PLS) analysis to assess the implications of this study. In result most hypotheses in our research model were statistically supported with the exception of one. Although one hypothesis was not supported, the study's findings provide us with some important implications. First the role of experience in IS continuance differs from its role in IS acceptance. Second, the use of IS was explained by the dynamic balance between habit and intention. Third, the importance of satisfaction was confirmed from the perspective of IS continuance with experience.