• Journal of Korean Library and Information Science Society
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• v.42 no.2
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• pp.323-341
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• 2011

In this study, the factor that affect use value of domestic public library was analysed. This study try to grasp the effect of various variables such as characteristics of the respondent and library through the measurement using CVM that extract the value by the user's statement. For this purpose, effective variables identified in the value measurement study of domestic and foreign public library was grasped and characteristics of the effective variables presented in the study examined. The factor influenced WTP representing library's value are the demographic characteristics such as gender, income, age and the using pattern such as frequency of use, time to visit. As to user's satisfaction and recognition, the recognition about librarian's satisfaction, place for resident's exchange, degree of financial support, culture-art volunteers are affecting depending on the service such as information, facilities and programs. The study comprehensively analysed the impact on the value measured by all types of public library in the nation and provided the information about property of value assessed by user according to region and scale. This information is expected to help the strategic policy making to enhance the value of library in the future.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.4
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• pp.709-720
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• 2024

By inputting consumer satisfaction as an exogenous variable into the value-based adoption model, this study explored the factors that influence the user's intention to continue using image-centered generative AI. Briefly presenting the main results, first, enjoyment did not significantly affect perceived value, but usefulness had a positive effect on perceived value. Second, Fee and technicality had a negative effect on perceived value. Third, perceived value had a positive effect on consumer satisfaction and continuous use intention. Fourth, consumer satisfaction had a positive effect on continuous use intention. Based on the above results, it is important to recognize the usefulness of image-centered generated AI and enjoyment in the process of use in order to increase the user's intention to continue using image-centered generated AI, and at the same time, it will be important to increase the user's perceived value and satisfaction by minimizing the reasonable fee and complexity in the method of use at the level acceptable to the users.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.58.2-58
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• 2001

• The Research Journal of the Costume Culture
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• v.22 no.1
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• pp.158-166
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• 2014

Apparel design is an economic activity to create values for users over the value chain of a product. In this paper, the contribution of apparel design is defined as the enhancement of users' perceived values by improving users' experience of products. In this context, the value of a product corresponds to compensation for experience or a promise for experience of a product. Experience can be sensory or psychological benefits to users. To evaluate the value of apparel design, the researcher identified and analyzed the apparel design parameters affecting users' experience and benefits of products such as macro-, micro-environmental factors, value chain factors, apparel designer factors, and user factors. For an analytical modeling of the values of apparel design, this paper introduces the concept of a utility function from economics. In economics, utility is a measure of desirability or satisfaction that can be correlative to need or desire. The measure of value can be found in the price which a user is willing to pay for the fulfillment or satisfaction of need or desire via the experience of a product.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.287-296
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• 2003

There has been much research focused on collaborative filtering technique in Recommender System. However, these studies have shown the First-Rater Problem and the Sparsity Problem. The main purpose of this Paper is to solve these Problems. In this Paper, we suggest the user's predicting preference method using Bayesian estimated value and the associative user clustering for the recalculation of preference. In addition to this method, to complement a shortcoming, which doesn't regard the attribution of item, we use Representative Attribute-Neighborhood method that is used for the prediction when we find the similar neighborhood through extracting the representative attribution, which most affect the preference. We improved the efficiency by using the associative user's clustering analysis in order to calculate the preference of specific item within the cluster item vector to the collaborative filtering algorithm. Besides, for the problem of the Sparsity and First-Rater, through using Association Rule Hypergraph Partitioning algorithm associative users are clustered according to the genre. New users are classified into one of these genres by Naive Bayes classifier. In addition, in order to get the similarity value between users belonged to the classified genre and new users, and this paper allows the different estimated value to item which user evaluated through Naive Bayes learning. As applying the preference granted the estimated value to Pearson correlation coefficient, it can make the higher accuracy because the errors that cause the missing value come less. We evaluate our method on a large collaborative filtering database of user rating and it significantly outperforms previous proposed method.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.525-536
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• 2021

This study investigated that customer satisfaction based on the effects of perceived value (innovative value, practical value, symbolic value) and innovation characteristics (innovative resistance, visibility) of wearable healthcare device users on purchase attitude. A survey was conducted on actual users who are currently using wearable healthcare devices, and the final 201 copies were analyzed using SPSS 25 and SmartPLS 3.0. The summary of research results is following here. First, it was found that the perceived values, innovative and practical values had a positive (+) effect on the user's purchasing attitude, while symbolic values did not affect the user's purchasing attitude. Second, among the innovation characteristics, innovation resistance was came out negative (-) effect on the user's purchasing attitude, and among the innovation characteristics, visibility did not affect the user's purchasing attitude. Third, it was found that perceived price had a positive (+) effect on the user's purchase attitude. Fourth, it was clarified that the perceived price and purchase attitude had a positive (+) effect on the user's customer satisfaction. Based on these research results, theoretical, practical, and future research directions were proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.9
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• pp.1590-1595
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• 2006

This paper proposes a technique of user oriented document ranking using user refile to provide more satisfied results which reflect preference of specific users. User profile is constructed to represent his or her preference. User pfofile consists of 'term array' and 'preference vector' according to the interest field of one. And the User profile for a particular person is updated by 'user access', 'latent relaeon', 'User Profile' proposed in this paper. The latent structures of documents in same domain are analysed by singular value decomposition(SVD). Then, the rank of documents is determined by comparison of user profile with analyzed document on the basis of relevance.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.3
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• pp.77-85
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• 2018

Multi-User Multiple-Input Multiple-Output (MU-MIMO) is the core technology for improving the channel capacity compared to Single-User MIMO (SU-MIMO) by using multiuser gain and spatial diversity. Key problem for the MU-MIMO is the user selection which is the grouping the users optimally. To solve this problem, we adopt Extreme Value Theory (EVT) at the beginning of the proposed algorithm, which defines a primary user set instead of a single user that has maximum channel power according to a predetermined threshold. Each user in the primary set is then paired with all of the users in the system to define user groups. By comparing these user groups, the group that produces a maximum sum rate can be determined. Through computer simulations, we have found that the proposed method outperforms the conventional technique yielding a sum rate that is 0.81 bps/Hz higher when the transmit signal to noise ratio (SNR) is 30 dB and the total number of users is 100.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.237-245
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• 2012

This study deals with the influencing factors for satisfaction and the emotional value perception of mobile voucher service user. Thus researcher examined a structural equation modeling methodology of the paths within word of mouth, satisfaction, and other exogenous variables (economic/rational value, trust, joyfulness, innovativeness). As a result of this study, First, it was confirmed that the emotional value, and innovativeness affected user's trust for coupon service and joyfulness for using mobile voucher. Second, it was confirmed that trust and joyfulness affected user's satisfaction and word of mouth activities. Therefore, in cases of utilizing the emotional appeal of mobile voucher as part of a marketing tool, corporate can maximize efficiency by using their mobile voucher service & event from the point of view of customer's satisfaction & voluntary word of mouth. Researcher's consideration is that this paper's theoretical and practical contribution point is the propose of the one of the post adoption model with the quantitative study of the mobile voucher service user's emotional perception in the initial development stages of high-tech industry.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.65-71
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• 2014

This paper present the multi-modal user distance estimation system using mono camera and mono microphone basically equipped with a mobile device. In case of a distance estimation method using an image, we is estimated a distance of the user through the skin color region extraction step, a noise removal step, the face and eyes region detection step. On the other hand, in case of a distance estimation method using speech, we calculates the absolute difference between the value of the sample of speech input. The largest peak value of the calculated difference value is selected and samples before and after the peak are specified as the ROI(Region of Interest). The samples specified perform FFT(Fast Fourier Transform) and calculate the magnitude of the frequency domain. Magnitude obtained is compared with the distance model to calculate the likelihood. We is estimated user distance by adding with weights in the sorted value. The result of an experiment using the multi-modal method shows more improved measurement value than that of single modality.