• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.512-520
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• 2009

Maximum intensity projection (MIP) is a volume rendering method which extracts maximum values along the viewing direction through volume data. It visualizes high-density structures, such as angio-graphic datasets so that it is frequently used in medical imaging systems. We have proposed an efficient two-step MIP acceleration method that uses the recent CPUs. First, we exploited SIMD instructions to reduce conditional branch instructions which take up a considerable part of whole rendering process, so that we improved rendering speed. Second, we proposed a new method, which accesses volume and image data successively by modifying the shear-warp rendering. This method improves memory access patterns so that cache misses are reduced. Using the current CPUs, our method improved the rendering speed by a factor of 7 than that of the shear-warp rendering.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.305-312
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• 2020

As a demand for a new video coding standard having higher coding efficiency than the existing standards is growing, recently, MPEG and VCEG has been developing and standardizing the next-generation video coding project, named Versatile Video Coding (VVC). Many inter prediction techniques have been introduced to increase the coding efficiency, and among them, an adaptive motion vector resolution (AMVR) technique has contributed on increasing the efficiency of VVC. However, the best motion vector can only be determined by computing many rate-distortion costs, thereby increasing encoding complexity. It is necessary to reduce the complexity for real-time video broadcasting and streaming services, but it is yet an open research topic to reduce the complexity of AMVR. Therefore, in this paper, an efficient technique is proposed, which reduces the encoding complexity of AMVR. For that, the proposed method exploits a special VVC tree structure (i.e., multi-type tree structure) to accelerate the decision process of AMVR. Experiment results show that the proposed decision method reduces the encoding complexity of VVC test model by 10% with a negligible loss of coding efficiency.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.7
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• pp.37-43
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• 2010

As the speed of A/V streaming, the transmission-speed requirement of serial link is continuously increasing. Consequently, commercial standards, which are released previously, are increasing transmission speed in their newly-updated versions. The flexibility between previous and updated versions is very important requirement, therefore, the transceiver which can operates at more than one data rate is important market demand. This paper demonstrates 4-channel 3.2/ 6.4 Gbps transmitter, which is capable of selecting 1, 1.5, 2, and 3 times of pre-emphasis and 200, 300, 400, and 600 mVdiff,p2p of output swing. The prototype chip was fabricated using $0.13{\mu}m$ CMOS process. Its performances are verified on PCB using COB packaging.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.114-116
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• 2016

Recently, SDN and NFV technology have been developed actively and provide enormous flexibility of network provisioning. The future network services would generally involve many different types of services such as hologram games, social network live streaming videos and cloud-computing services, which have dynamic service requirements. To provision networks for future services dynamically and efficiently, SDN/NFV orchestrators must clearly understand the service requirements. Currently, network provisioning relies heavily on QoS parameters such as bandwidth, delay, jitter and throughput, and those parameters are necessary to describe the network requirements of a service. However it is often difficult for users to understand and use them proficiently. Therefore, in order to maintain interoperability and homogeneity, it is required to have a service abstraction layer between users and orchestrators. The service abstraction layer analyzes ambiguous user's requirements for the desired services, and this layer generates corresponding refined services requirements. In this paper, we present our initial effort to design a Smart Service Abstraction Layer (SmSAL) for future network architecture, which takes advantage of machine learning method to analyze ambiguous and abstracted user-friendly input parameters and generate corresponding network parameters of the desired service for better network provisioning. As an initial proof-of-concept implementation for providing viability of the proposed idea, we implemented SmSAL with a decision tree model created by learning process with previous service requests in order to generate network parameters related to various audio and video services, and showed that the parameters are generated successfully.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.721-732
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• 2000

Multimedia communication systems require not only high-performance computer hardwares and high-speed networks, but also a buffer management mechanism to process many data efficiently. Two buffer handling methods, Push and Pull, are commonly used. In the Push method, a server controls the flow of dat to a client, while in the Pull method, a client controls the flow of data from a server. Those buffering schemes can be applied to the data transfer between the packet receiving buffer, which receives media data from a network server, and media playout devices, which play the recived media data. However, the buffer management mechanism in client-sides mainly support either one of the Push or the Pull method. Consequently, they have some limitations to support various media playout devices. Futhermore, even though some of them support both methods, it is difficult to use since they can't provide a unified structure. To resolved these problems, in this paper, we propose an efficient and flexible Push/Pull buffer management mechanism at client-side. The proposed buffer management scheme supports both Push and Pull method to provide various media playout devices and to support buffering function to absorb network jitter. The proposed scheme can support the various media playback devices using a single buffer space which in consequence, saves memory space compared to the case that a client keeps tow types of buffers. Moreover, it facilitates the single buffer as a mechanism for the absorbing network jitter effectively and efficiently. The proposed scheme has been implemented in an existing multimedia communication system, so called ISSA (Integrated Streaming Service Architecture), and it shows a good performance result compared to the conventional buffering methods in multimedia communication environments.

• Journal of the Korean Society for information Management
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• v.32 no.2
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• pp.221-236
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• 2015

This paper describes the process and methodology followed in developing the Android-based LG Sangnam Audiobook service and an evaluation of its usefulness to the public. The methods included a survey of user needs, analysis of usage statistics, and user interviews. The study found that visually impaired users: 1) were greatly interested and willing to use smartphones if there were no barrier in cost and access; 2) preferred downloads to streaming services; 3) did not mind performance differences between real and TTS (text-to-speech) voices; 4) showed marked differences in book preferences according to age, 5) made about 14,000 downloads in 2014; and 6) indicated bookmarking and moving between pages and tables of content as the most important functions in using audiobooks.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.11
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• pp.658-672
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• 2004

Multimedia applications are required to process the huge amount of data at high speed in real time. The memory reference instructions such as loads and stores are the main factor which limits the high speed execution of processor. To enhance the memory reference speed, cache prefetch schemes are used so as to reduce the cache miss ratio and the total execution time by previously fetching data into cache that is expected to be referenced in the future. In this study, we present an advanced data cache prefetching scheme that improves the conventional RPT (reference prediction table) based scheme. We considers the cache line size in calculation of the address stride referenced by the same instruction, and enhances the prefetching algorithm so that the effect of prefetching could be maintained even if an irregular address stride is inserted into the series of uniform strides. According to experiment results on multimedia benchmark programs, the cache miss ratio has been improved 29% in average compared to the conventional RPT scheme while the bus usage has increased relatively small amount (0.03%).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.1998-2004
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• 2009

Recently, due to technical developments of various storage devices and networks, the amount of data increases rapidly. The large volume of data streams poses unique space and time constraints on the data mining process. The continuous characteristic of streaming data necessitates the use of algorithms that require only one scan over the stream for knowledge discovery. Most of the researches based on the support are concerned with the frequent itemsets, but ignore the infrequent itemsets even if it is crucial. In this paper, we propose an efficient method WSFI-Mine(Weighted Support Frequent Itemsets Mine) to mine all frequent itemsets by one scan from the data stream. This method can discover the closed frequent itemsets using DCT(Data Stream Closed Pattern Tree). We compare the performance of our algorithm with DSM-FI and THUI-Mine, under different minimum supports. As results show that WSFI-Mine not only run significant faster, but also consume less memory.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.27-32
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• 2019

Research that implements the classification process through Deep Learning algorithm, one of the outstanding human abilities, includes a unimodal model, a multi-modal model, and a multi-modal method using music videos. In this study, the results were better by suggesting a system to analyze each song's spectrum into short samples and vote for the results. Among Deep Learning algorithms, CNN showed superior performance in the category of music genre compared to RNN, and improved performance when CNN and RNN were applied together. The system of voting for each CNN result by Deep Learning a short sample of music showed better results than the previous model and the model with Softmax layer added to the model performed best. The need for the explosive growth of digital media and the automatic classification of music genres in numerous streaming services is increasing. Future research will need to reduce the proportion of undifferentiated songs and develop algorithms for the last category classification of undivided songs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.5
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• pp.47-58
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• 2011

Recently, there are several technologies for protecting information in the lightweight device, One of them, the AES[1] algorithm and CRT mode, is used for numerous services(e,g, OMA DRM, VoIP, IPTV) as encryption technique for preserving confidentiality. Although it is possible that the AES algorithm CRT mode can parallel process transmitting data, IPTV Set-top Box or Mobile Device that uses these streaming service has limited computation-ability. So optimizing crypto algorithm and enhancing its efficiency for those environment have become an important issue. In this paper, we propose implementation method that can improve efficiency of the AES-CRT Mode by improving algorithm logics. Moreover, we prove the performance of our proposal on the mobile device which has limited capability.