• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.553-563
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• 2019

As the number of videos uploaded on live streaming platforms rapidly increases, the demand for providing highlight videos is increasing to promote viewer experiences. In this paper, we present novel methods for predicting highlights using chat logs and audio data in videos. The proposed models employ bi-directional LSTMs to understand the contextual flow of a video. We also propose to use the features over various time-intervals to understand the mid-to-long term flows. The proposed Our methods are demonstrated on e-Sports and baseball videos collected from personal broadcasting platforms such as Twitch and Kakao TV. The results show that the information from multiple time-intervals is useful in predicting video highlights.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.82-85
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• 2014

With high speed communication network and supplement of high quality multimedia devices, large demand of multimedia service stimulates digital signing industry to step forward to new opportunities. But in order to provide competitive quality services, Integrated management system is required. Digital signs use technologies such as LCD, LED and Projection to display content such as digital images, video, streaming media, and information. Digital signs rely on a variety of hardware to deliver the contents. The components of a typical digital sign installation include one or more display screens, one or more media players, and a content management server for each player. To improve the existing high cost and less efficient management system, this paper suggest cost effective Integrated Digital Signage Management System with the results of analysis of existing system. Also this paper presents an actual implementation on entertainment company to evaluate the suitability, to prove the result of superior performance of proposed system.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.137-142
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• 2021

Distance learning universities provide online course content. The main methods of providing class contents are on-demand and live-streaming. This means that students are not restricted by time or space. The advantage is that students can take the course anytime and anywhere. Therefore, unlike commuting students, there is no commuting time to the campus, and there is no natural process required to take classes. However, despite this convenient situation, the attendance rate and graduation rate of distance learning universities tend to be lower than that of commuting universities. Although the course environment is not the only factor, students cannot obtain a bachelor's degree unless they fulfill the graduation requirements. In both commuter and distance learning universities, taking classes is an important factor in earning credits. There are fewer time and space constraints for distance learning students than for commuting students. It is also easy for distance learning students to take classes at their own timing. There should be more ease of learning than for students who commute to school with restrictions. However, it is easier to take a course at a commuter university that conducts face-to-face classes. I thought that the reason for this was that commuting to school was a part of the process of taking classes for commuting students. Commuting to school was thought to increase the willingness and motivation to take classes. Therefore, I thought that the inconvenient constraints might encourage students to take the course. In this research, I focused on the act of commuting to school by students. These situations are also applied to the distance learning environment. The students have physical time constraints. To achieve this goal, I will implement a course restriction method that aims to promote the willingness and attitude of students. Therefore, in this paper, I have implemented a virtual school system called "virtual go to school (VG2S)" that reflects the actual route to school.

• Journal of Powder Materials
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• v.30 no.3
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• pp.268-275
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• 2023

The demand for energy is steadily rising because of rapid population growth and improvements in living standards. Consequently, extensive research is being conducted worldwide to enhance the energy supply. Transpiration power generation technology utilizes the vast availability of water, which encompasses more than 70% of the Earth's surface, offering the unique advantage of minimal temporal and spatial constraints over other forms of power generation. Various principles are involved in water-based energy harvesting. In this study, we focused on explaining the generation of energy through the streaming potential within the generator component. The generator was fabricated using sugar cubes, PDMS, carbon black, CTAB, and DI water. In addition, a straightforward and rapid manufacturing method for the generator was proposed. The PDMS generator developed in this study exhibits high performance with a voltage of 29.6 mV and a current of 8.29 µA and can generate power for over 40h. This study contributes to the future development of generators that can achieve high performance and long-term power generation.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.842-848
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• 2020

Music markets have entered the era of streaming. In order to select and propose music that suits the taste of music consumers, there is an active demand and research on an automatic music genre classification system. We propose a method to improve the accuracy of genre unclassified songs, which was a lack of the previous system, by using a generative adversarial network (GAN) to further develop the automatic voting system for deep learning music genre using Softmax proposed in the previous paper. In the previous study, if the spectrogram of the song was ambiguous to grasp the genre of the song, it was forced to leave it as an unclassified song. In this paper, we proposed a system that increases the accuracy of genre classification of unclassified songs by converting the spectrogram of unclassified songs into an easy-to-read spectrogram using GAN. And the result of the experiment was able to derive an excellent result compared to the existing method.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.3
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• pp.140-148
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• 2009

Recent advances in communication and multimedia technologies make it possible to provide video-on-demand(VOD) services and people can access video servers over the Internet at any time using their electronic devices, such as PDA, mobile phone and digital TV. Each device has different processing capabilities, energy budgets, display sizes and network connectivities. To support such diverse devices, multiple versions of videos are needed to meet users' requests. In general cases, VOD servers cannot store all the versions of videos due to the storage limitation. When a device requests a stored version, the server can send the appropriate version immediately, but when the requested version is not stored, the server first converts some stored version to the requested version, and then sends it to the client. We call this conversion process transcoding. If transcoding occurs frequently in a VOD server, the CPU resource of the server becomes insufficient to response to clients. Thus, to admit as many requests as possible, we need to maximize the CPU availability. In this paper, we propose a new algorithm to select versions from those stored on disk using a branch and bound technique to maximize the CPU availability. We also explore the impact of these storage management policies on streaming to heterogeneous users.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.335-341
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• 2014

To play the networked video contents in a client's mobile device in real time, the contents should be delivered to it by the contents server with streaming technology. Generally, in a server-client based commerce model, the server is in charge of both the authentication of the paid customer and distribution of the contents. The drawback of it is that if the customers' requests go on growing rapidly, the service quality would be degraded results from the problems of overloaded server or restricted network bandwidth. On the contrary, in P2P based networks, more and more the demand for service increasing, the service quality is upgraded since a customer can act as a server. But, in the P2P based network, there are too many servers to manage, it's possible to distribute illegal contents because the P2P protocol cannot control distributed servers. Thus, it's not suitable for commercial purposes. In this paper, the dymanic group authentication scheme is proposed which is suited to P2P based applications. The proposed scheme consists of group based key generation, key update, signature generation and verification protocols. It can control the seeder's state whether the seeder is joining or leaving the network, and it can be applied to hybrid P2P based commerce model where sales transactions are covered by the index server and the contents are distributed by the P2P protocol.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.609-619
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• 2020

In accordance with a demand for high quality video streaming, it needs high data rate in limited bandwidth and more traffic congestion occurs. In particular, when providing real time video service, packet loss rate and bit error probability increase significantly. To solve these problems, a raptor code, which is one of FEC(Forward Error Correction) techniques, is pervasively used in the application layers as a method for improving real-time service quality. In this paper, we propose a method of determining image transmission parameters based on various deep neural networks to increase transmission efficiency at a similar level of image quality by using raptor codes. The proposed neural network uses the packet loss rate, video encoding rate and data rate as inputs, and outputs raptor FEC parameters and packet sizes. The results of the proposed method present that the throughput is 1.2% higher than that of the existing multimedia transmission technique by optimizing the transmission efficiency at a PSNR(Peak Signal-to-Noise Ratio) level similar to that of the existing technique.