• Science of Emotion and Sensibility
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• v.26 no.4
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• pp.3-14
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• 2023

Recently, the effect of using social media on psychological well-being has been highlighted. However, studies exploring factors that may predict the quality of social media relationships are relatively rare. The present study investigated whether social media activity and psychological states, such as loneliness and depression, can predict the quality of social media relationships during the COVID-19 quarantine period using a machine learning technique. Ninety-five participants completed a self-report survey on loneliness, Instagram activity, quality of social media relationships, and depression at different time points (during the self-isolation and after the release of self-isolation). Similarity analyses, including multidimensional scaling (MDS), representational similarity analysis (RSA), and classification analyses, were conducted separately at each point in time. The results of MDS revealed that time spent on social media and depression were distinguished from others in the first dimension, and loneliness and passive use were distinguished from others in the second dimension. We divided the data into two groups based on the quality of social media relationships (high and low), and we conducted RSA on each group. Findings indicated an interaction between the quality of the social media relationships and the situation. Specifically, the effect of self-isolation on the high-quality social media relationship group is more pronounced than that on the low-quality group. The classification results also revealed that the predictors of social media relationships depend on whether or not they are isolated. Overall, the results of this study imply that social media relationship could be well predicted when people are not in isolated situations.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.287-295
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• 2015

The IPTV service has to be converted into an unified media format that fits for a variety of terminal equipments in terms of the bulk high-capacity media contents, and is spending a lot of time in the conversion time of contents including the process of collecting the media contents and extracting the information for conversion. In order to solve the problem, this paper designed the database in accordance with the automatic collection of time, and proposed a system that could increase the productivity of the contents through the automation process of the entire process using the media server and the transcoder. The media server collected contents and extracted information automatically with respect to the contents servers placed in specific locations and the media files of the storage whereas the transcoder conducted the automatic upload of the converted results to a specific server through the process of automatic conversion. As a result, the various convergence through compared to existing conversion method could minimized unnecessary waste of time.

• Journal of Korea Multimedia Society
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• v.20 no.10
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• pp.1646-1654
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• 2017

Pupil size variation can not be controlled intentionally by the user and includes various features such as the blinking frequency and the duration of a blink, so it is suitable for understanding the user's emotional state. In addition, an ocular feature based emotion classification method should be studied for virtual and augmented reality, which is expected to be applied to various fields. In this paper, we propose a novel emotion classification based on CNN with pupil size variation signals which include not only various ocular feature information but also time information. As a result, compared to previous studies using the same database, the proposed method showed improved results of 5.99% and 12.98% respectively from arousal and valence emotion classification.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.471-477
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• 2017

This paper deals with the viewing rate trends of digital media service special reference to terrestrial real time broadcasting of IPTV. In a few years, TV viewership of young people is decreasing, the audience viewing rate of the terrestrial broadcasting which is the representative of the media decreases, and the change of the broadcasting industry is progressing. Especially after the terrestrial broadcaster 's VOD holdback was extended, the viewer' s movement on the competitive channel & mobile media was rapidly progressing. Researcher assumed that the viewing rate of the terrestrial real-time broadcasting has influenced the comprehensive channel, CJ E&M subsidiary channels. As a result, researcher verified using statistical methodological time series analysis and regression analysis. Based on these results, researcher expects media players to prepare policies for viewers' satisfaction and symbiotic growth of markets.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.366-374
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• 2017

Since a display device such as TV or digital signage is getting larger, the types of media is getting changed into wider view one such as UHD, panoramic and jigsaw-like media. Especially, panoramic and jigsaw-like media is realized by stitching video clips, which are captured by different camera or devices. However, a stitching process takes long time, and has difficulties in applying for a real-time process. Thus, this paper suggests to find out 2D Adjacency Matrix, which tells spatial relationships among those video clips in order to decrease a stitching processing time. Using the Discrete Cosine Transform (DCT), we convert the each frame of video source from the spatial domain (2D) into frequency domain. Based on the aforementioned features, 2D Adjacency Matrix of images could be found that we can efficiently make the spatial map of the images by using DCT. This paper proposes a new method of generating 2D adjacency matrix by using DCT for producing a panoramic and jigsaw-like media through various individual video clips.

• KSCI Review
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• v.2 no.2
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• pp.27-40
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• 1996

During the 21st century of informational society, in the learning of various field will utilize the education using multi-media more extensively than ever before. The biggest question is how effective the education using multi-media will be. For effective education, wide-spread supply of not only the hardware and various kinds of CBT or CAI that are being developed in the learning of various fields. It is also felt that the skill for application of more convenient multi-media authoring tool is needed. If the producter of such multi-media authoring tool can store various types of information in a form of data bank, accessing the right information at right time and its application would be possible. It can also provide a lot of information to many out-of town learmers. As seen above, the scope of usage for multi-media authoring tool will be broadened. However, no matter how excellent the Authoring Tool is, the results can be very different depending on the method employed. In order to develop CBT or CAI that can be better used in the learning of various fields, examination and on-site training, more reseach should be done in Authoring Tool using virtual reality and artifical intelligence technology.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3195-3200
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• 2000

this paper is a stucy onthe preductionof multi-media traffic flow for the realizationof optimum ATM congestion control. In ATM network it is expected that the characteristic of multi-media traffic flow is varied slowly with a time. Fjor the simulation, time-variable multi-media traffic is penerated using possion distribution(connect calls per process time).\, gamma distribution(transmission rate per a call) and exponential distribution(holding time per a call). And using back-propagation neural netwok and proposed tripple neural network, the simulation to predict generaed traffic is executed. From the result,it's capability is shown that the proposed neural network model can be used in the predictionof ATM traffic flow.

• Journal of the Korean GEO-environmental Society
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• v.2 no.1
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• pp.31-35
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• 2001

The effects of the ratio of effective size of filter media and diatom size on filter run time were evaluated by using both reported data and experimental results from several water treatment plants. For single media at several WTPs, the range of probability of the filter run time less than 15hr was 10~60%, and for dual media, that of the filter run time less than 30hr was 10~20%. The major filter clogging algae was Synedra acus of which dominant ratio was in the range of 64~92%. The effective size(ES) of filter medium for dual media filter was 0.71~1.40mm and uniformity coefficient of the filter was 1.25~1.67. The effective size(ES) of filter medium for single medium filter was 0.52~0.65mm and uniformity coefficient of the filter was 0.25~1.40. The range of calculated penetration depth was 2.58~15.4cm for dual media and 1.29~2.17cm for single media, and average filter run time was 40.1~83.3hr and 13.9~34.9hr, respectively. When Synedra counts were over 400cells/ml for single media, filter run time was below 5hr, while filter run time for dual media filter, remained as high as 70hr.

• The Journal of Information Systems
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• v.32 no.3
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• pp.165-181
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• 2023

Purpose Digital platforms, together with the innovative technologies of modern society, are accelerating the digital innovation of the entire economy and society. Although social media platforms are gradually integrated into daily life, due to social media overload, users limit their use of the platform for a certain period of time or eventually choose to stop using it. In the context of social media platform, the purpose of this paper is to study the effects of information overload, social overload and system function overload on users' unintentional avoidance behavior, mediated by fatique and dissatisfaction. Design/methodology/approach This study empirically examines the influence of social media overload characteristics on users' unintentional avoidance behavior of platform utilization using the S-O-R framework. Data from 236 Chinese social media users were collected through a questionnaire survey, and the hypotheses were validated by evaluating the research model using the SmartPLS 4.0 program using Partial Least Square (PLS) method. Findings According to the empirical analysis result, based on the S-O-R model, first, it is confirmed that information overload and system feature overload have significant positive(+) effects on fatigue. Second, this study finds that information overload, social overload and fatigue have significant positive(+) effects on dissatisfaction. Thirdly, fatigue and dissatisfaction have significant positive(+) effects on unintentional avoidance. In addition, social overload has no significant effect on fatigue, while system feature overload has no significant effect on dissatisfaction.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.109-112
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• 2020

Many devices are connected on the internet to give functionalities for interconnected services. In 2020', The number of devices connected to the internet will be reached 5.8 billion. Moreover, many connected service provider such as Google and Amazon, suggests edge computing and mesh networks to cope with this situation which the many devices completely connected on their networks. This paper introduces the current state of the introduction of the wireless mesh network and edge cloud in order to efficiently manage a large number of nodes in the exploding Internet of Things (IoT) network and introduces the existing Network Time Protocol (NTP). On the basis of this, we propose a relatively accurate time synchronization method, especially in heterogeneous mesh networks. Using this NTP, multiple time coordinators can be placed in a mesh network to find the delay error using the average delay time and the delay time of the time coordinator. Therefore, accurate time can be synchronized when implementing IoT, remote metering, and real-time media streaming using IoT mesh network.