• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.495-496
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• 2014

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.5
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• pp.326-338
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• 2006

In this paper, we propose the weighted Markov model for recommending the users' prefered contents in the environment with considering the users' transition of their content consumption mind according to the kind of contents providing in time. In general, TV viewers have an intention to consume again the preferred contents consumed in recent by them. In order to take into the consideration, we modify the preference transition matrix by providing weights to the consecutively consumed contents for recommending the users' preferred contents. We applied the proposed model to the recommendation of TV viewer's genre preference. The experimental result shows that our method is more efficient than the typical methods.

• Journal of Agricultural Extension & Community Development
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• v.16 no.2
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• pp.463-486
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• 2009

The purpose of this study was to find out the differences of preferences in e-Learning contents delivery types according to information searching retrieval ability in agricultural high school students. Contents delivery types are limited three kinds which are HTML type, video type, and text type and need to know about differences. The following summarizes the results of this study. On the preference of e-Learning contents delivery type on information searching retrieval ability had differences. High level group of information searching retrieval ability showed that they mostly preferred text contents delivery type. However, low level group of information searching retrieval ability showed that they preferred video contents delivery type. The results support our belief that there could be the differences in preferences in e-Learning delivery types with students' information searching retrieval abilities. We suggest that delivery types of e-Learning should be based on the students not on designers and developers.

• The Journal of the Acoustical Society of Korea
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• v.23 no.6
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• pp.437-445
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• 2004

In this paper. we describe a novel method for transforming audio contents according to user's preference on sound field. Sound field effect technologies. which transform or simulate acoustic environments as user's preference, are very important for enlarging the reality of acoustic scene. However huge amount of computational power is required to process sound field effect in real time. so it is hard to implement this functionality at the portable audio devices such as MP3 player. In this paper, we propose an efficient method for providing sound field effect to audio contents independent of terminal's computational power through processing this functionality at the server using user's sound field preference, which is transfered from terminal side. To describe sound field preference, user can use perceptual acoustic parameters as well as the URI address of room impulse response signal. In addition, a novel fast convolution method is presented to implement a sound field effect engine as a result of convoluting with a room impulse response signal at the realtime application. and verified to be applicable to real-time applications through experiments. To verify the evidence of benefit of proposed method we performed two subjective listening tests about sound field descrimitive ability and preference on sound field processed sounds. The results showed that the proposed sound field preference can be applicable to the public.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.12 no.1
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• pp.20-28
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• 2018

In this research, for the smooth cultural life of seniors, we recruit 92 smart seniors (male: 22, female: 70) and survey their preferred content sub-genre. The survey is mainly based on the two devices (PC, Smartphone) to be used. As a result of the study, there was a little difference in preference on the web pages between both devices, the video contents showed the similar preference, regardless of the device. Also, sub-genres surveyed show higher correlations with similar sub-genres in other content genres. So, If the result of this study is reflected in the development of cultural contents and the composition of content pages, it will be helpful for senior to enjoy the improved cultural life by lowering entry barriers accessing digital media contents.

• Journal of Advanced Navigation Technology
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• v.13 no.2
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• pp.296-301
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• 2009

In the self-directed learning, learner can construct learning course. But it is very difficult for learner to construct learning course with understanding the various learning contents's characteristics. This research proposed the method to support to learner the information of learning contents type to fit the learner as calculate the learner's learning preference when learner construct the learning course. The calculating method of learning preference used preference vector value of topic map. To apply this method, we tested 20 learning sampling group and presented that this method help to learner to construct learning course as getting the high average degree of learning satisfaction.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2002.11a
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• pp.243-246
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• 2002

It is expected that intelligent broadcasting service (IBS) will be able to provide broadcast programs based on user preference and program-associated information (metadata) in order to assist users to easily navigate the program contents being broadcast. So users can access program contents anytime/anywhere in the way they want. In this paper we propose a framework for IBS based on an intelligent software agent platform so called FIPA (Foundation for Intelligent Physical Agents). We use an FIPA implementation. so called FIPA-OS, as a platform for exchanging user preferences and program information as FIPA messages between a server and clients. The user preference is modeled as the User Preference description scheme in MPEG-7 MDS (Multimedia Description Scheme).

• International Journal of Contents
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• v.11 no.2
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• pp.20-30
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• 2015

We propose a new method that specifies objective image quality factors by evaluating an image quality measurement model using random images. In other words, No-Reference variables are used to evaluate the quality of an original image without using any reference for comparison. 1000 portrait images were collected from a web gallery with votes constituting over 30 recommendation values. The bottom-up data collecting process was used to calculate the following image quality factors: total range, average, standard deviation, normalized distribution, z-score, preference percentage. A final grade is awarded out of 100 points, and this method ranks and grades the final estimated image quality preference in terms of total image quality factors. The results of the proposed image quality evaluation model consist of the specific dynamic range, skin tone R, G, B, L, A, B, and RSC contrast. We can present the total for the expected preference points as the average of the objective image qualities. Our proposed image quality evaluation model can measure the preferences for an actual image using a statistical analysis. The results indicate that this is a practical image quality measurement model that can extract a subject's preferred image quality.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.1-8
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• 2008

The information system in which users can utilize to control and to get the filtered information efficiently has appeared. Content-based filtering can reflect content information, and it provides recommendation by comparing the feature information about item and the profile of preference. This has the shortcoming of the varying accuracy of prediction depending on teaming method. This paper suggests the discovery of preference through learning the profile for the content-based filtering. This study improves the accuracy of recommendation through learning the profile according to granting the preference of 6 levels to estimated value in order to solve the problem. Finally, to evaluate the performance of the proposed method, this study applies to MovieLens dataset, and it is compared with the performance of previous studies.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.236-247
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• 2021

The purpose of the study was to investigate the influencing factors of autonomy preference on decision-making among chronic disease patients. Data were collected from 522 chronic disease patient and it was analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation coefficients, and multiple linear regression, using SPSS 26.0 ver. program. Significant factor influencing decision-making preference was health concern (β=-.17, p<.001), and factors influencing information-seeking preference were gender (β=-.20, p<.001) and number of questions during the treatment (β=.09, p=.030). Healthcare providers should take into account the characteristics of patients and establishment of a strategy to improve the quality of communication.