• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3635-3654
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• 2015

With the rapid development of smart devices and mobile Internet, the video application plays an increasingly important role on mobile devices. Understanding user behavior patterns is critical for optimized operation of mobile live streaming systems. On the other hand, volume based billing models on cloud services make it easier for video service providers to scale their services as well as to reduce the waste from oversized service capacities. In this paper, the watching behaviors of a commercial mobile live streaming system are studied in a content-centric manner. Our analysis captures the intrinsic correlation existing between popularity and watching intensity of programs due to the synchronized watching behaviors with program schedule. The watching pattern is further used to estimate traffic volume generated by the program, which is useful on data volume capacity reservation and billing strategy selection in cloud services. The traffic range of programs is estimated based on a naive popularity prediction. In cross validation, the traffic ranges of around 94% of programs are successfully estimated. In high popularity programs (>20000 viewers), the overestimated traffic is less than 15% of real happened traffic when using upper bound to estimate program traffic.

• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.338-345
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• 2011

Nowadays mobile devices are used for various applications such as making voice/video calls, browsing the Internet, listening to music etc. The average battery consumption of each of these activities and the length of time a user spends on each one determines the battery lifetime of a mobile device. Previous methods have provided predictions of battery lifetime using a static battery consumption rate that does not consider user characteristics. This paper proposes an approach to predict a mobile device's available battery lifetime based on usage patterns. Because every user has a different pattern of voice calls, data communication, and video call usage, we can use such usage patterns for personalized prediction of battery lifetime. Firstly, we define one or more states that affect battery consumption. Then, we record time-series log data related to battery consumption and the use time of each state. We calculate the average battery consumption rate for each state and determine the usage pattern based on the time-series data. Finally, we predict the available battery time based on the average battery consumption rate for each state and the usage pattern. We also present the experimental trials used to validate our approach in the real world.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.10
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• pp.684-690
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• 2014

In this work we investigate the benefit of multicast in the delivery of video data over the mobile MBMS network. In order to quantify the benefit in a practical aspect, this work proposes an analytic framework that employs a combined statistical and queuing model, where a queuing model represents the behavior of user's access to the video service and the statistical model captures the popularity of the video contents, via which we draw out a more realistic intuition for the expected benefit from multicast. Finally, we present results of numerical experiment that illustrates the validity of the proposed work.

• Journal of Information Technology Applications and Management
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• v.17 no.2
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• pp.111-132
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• 2010

Korean telecommunications industry has a large scale market and boasts on high service quality and high technologies enough to provide the mobile video telephony service(the VTS) satisfactorily. For many years, Korean telecommunications companies have been investing enormous amount of money to advertise their VTS widely and to allow their customers to change their cell phones for the 3G(the third generation) devices indispensable for the VTS. However, despite their efforts, the VTS adoption rate in Korea is very low as of January, 2010 and it seems that customers seldom feel the necessity to use. From this viewpoint, it becomes necessary to identify antecedents influencing the intention to use for the VTS empirically. For this purpose, we have proposed several hypotheses from the perspective of the Value-based Adoption Model(VAM). We conducted a survey and found the several factors which influence the value perception of VTS.

• Journal of KIISE:Information Networking
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• v.35 no.6
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• pp.510-520
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• 2008

These days, the network convergence for utilizing heterogeneous network on mobile device is being very actively studied. However, understanding characteristics of physical network interfaces and video encoder is needed for using the network convergence technologies efficiently. Thus, this paper proposes an optimized method for streaming video data through different network paths depending on data characteristics and channel condition. Accordingly, unlike the traditional methods, this study divides scalable coded videos by layer importance, the importance of stream information, and the importance in consideration of video decoder's robustness and selectively sends the data via multiple channels. And the experimental results show over 1dB increment in PSNR. The result of this study will provide an optimized video transmission technique in the next generation network convergence environment in which mobile devices have multiple network interfaces.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.1
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• pp.1-9
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• 2007

Digital Multimedia Broadcasting is the next generation broadcasting service which enables various digital multimedia contents, i.e., audio and video, and data access for mobile users. However, due to the bandwidth limitation, the spatial resolution is limited to CIF(Common Interleaved Frame). The Advanced Terrestrial DMB (AT-DMB) secures additional bandwidth by adopting hierarchical modulation transmission technology and provides high data rate and quality for mobile multimedia broadcasting services with scalable video coding(SVC). This paper proposes scalable video coding technology for AT-DMB which enables high quality mobile multimedia broadcasting services that exceeds current DMB service's quality and contents capability.

• Journal of Information Technology Applications and Management
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• v.17 no.1
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• pp.107-125
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• 2010

The purpose of this research is to identify the critical factors influencing on the continuous use of video telephony service for mobile devices. An empirical analysis has been performed by using service quality, brand image, price, fun as influencing factors, and satisfaction and commitment as mediating factors. The partial least squares(PLS) methodology with 228 questionnaires has been conducted. The results indicated that brand image, price, and fun were mediated by satisfaction and commitment to have a statistically significant influence on continuous use of video telephony service. Service quality showed a significant effect on continuous use mediated by satisfaction while it did not show any influence through commitment. Based on the results, companies in the communication service industry should consider and focus on the improved brand image, appropriate fees, and individual preferences for fun for the successful marketing activities, and should also maintain amicable relations with their customers.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.352-354
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• 2005

As further Studies on 4th generation mobile telecommunication are progressed, the importance of a Cross-Layer is being increased. However, it has focused on coordination model only between MAC layer and PHY layer. It is necessary to expand into II' layer and upper layers. In this paper, we introduce a Cross-layer optimization which can be used to transmit video data with effect by managing resources among layers. It can gives further more adaptive method to solve QoS model problem than single layer.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.9-15
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• 2013

In this paper, automatic recognition of an accident and whether service delivery and risk driving through the giving of the driver to correct driving habits before and after the accident to reproduce highly scalable video Smart Mobile Blackbox DVR (SMBD, Smart Mobile Blackbox DVR) Computer of the model was designed. SMBD on embedded systems equipped with wireless capabilities to sleep in the car accident point and the image information by wireless communications, by notification in the control center, 24-hour emergency rescue service and traffic information can be provided. The vehicle ECU (Electronic Control Unit) of the vehicle information and sensor data in conjunction with wireless eCall (Emergency Call) services can be realized.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.230-240
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• 2022

Sharing of online videos via internet is an emerging and important concept in different types of applications like surveillance and video mobile search in different web related applications. So there is need to manage personalized web video retrieval system necessary to explore relevant videos and it helps to peoples who are searching for efficient video relates to specific big data content. To evaluate this process, attributes/features with reduction of dimensionality are computed from videos to explore discriminative aspects of scene in video based on shape, histogram, and texture, annotation of object, co-ordination, color and contour data. Dimensionality reduction is mainly depends on extraction of feature and selection of feature in multi labeled data retrieval from multimedia related data. Many of the researchers are implemented different techniques/approaches to reduce dimensionality based on visual features of video data. But all the techniques have disadvantages and advantages in reduction of dimensionality with advanced features in video retrieval. In this research, we present a Novel Intent based Dimension Reduction Semi-Supervised Learning Approach (NIDRSLA) that examine the reduction of dimensionality with explore exact and fast video retrieval based on different visual features. For dimensionality reduction, NIDRSLA learns the matrix of projection by increasing the dependence between enlarged data and projected space features. Proposed approach also addressed the aforementioned issue (i.e. Segmentation of video with frame selection using low level features and high level features) with efficient object annotation for video representation. Experiments performed on synthetic data set, it demonstrate the efficiency of proposed approach with traditional state-of-the-art video retrieval methodologies.