• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.253-261
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• 2006

In spite of the popularity of P2P technology, a multimedia streaming using the P2P technology has been neglected. The reason for this is that the P2P multimedia streaming has suffered from several inherent problems especially poor bandwidth and unreliable connection among peers. We suggest a Multi-Peer Binding Protocol (MPBP) in this paper that provides a virtual single channel composed of multiple connections to several peers to ease these problems. The protocol enables applications to download data from multiple peers simultaneously, so they can achieve throughput improvement and reliable streaming. For this, the MPBP splits media files into small chunks and provides a mechanism for identifying and transmitting each chunk. Implemented MPBP engine focuses on handling an abrupt disconnection from data sending peers and the evaluation result shows the MPBP is able to handle it gracefully. The MPBP is also desisted to support various media types. To verify this, video and audio applications are implemented using the MPBP engine in this paper.

• The Transactions of the Korea Information Processing Society
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• v.4 no.5
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• pp.1153-1161
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• 1997

In this paper, we propose Teloemedicine system on CBM(Computer Based Multimedia) based collaborative multimedia which supports special medicine and collaborative medicine with DB, face-to-face dffedt.This system is an application developed by SDK (Software Development Kit) of DooRae(Distributed Objected Oriented Multimedia Application Crafting Environment for Collaborative)framework.And this system is devel-Oriented Multimedia Applecation Crafting Environment for Collaborative) framework, And this system is devel-oped on windows 95 and windows NT.The scenario of this system is limited within only hospital(LAN), but it is possibloe to support many applications development in various nerwork(MAN, PSYN, WAN)on DooRae.This system has a smoth interaction by video and audio, multiple session, multiple participation, application sharing, toolbox including ICON and whiteboard.Also this system supports realo or non-real type without con-straint of the and space.

• Journal of the Korea Society of Computer and Information
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• v.7 no.3
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• pp.80-91
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• 2002

A general goal of the AT%(Asynchronous Transfer Mode) network is to support connect across various network. On ATM networks, ABR services are provided using the remained ban after allocation CBR and VBR traffic. Realtime services such as transmitting audio or video data may be provided using CBR ado VBR which have a constrained transmission delay, but in these cases, the communications bandwidth may be wasted. In this paper a simulation has been performed to compare and evaluate the performance between the ERICA(Explicit Rate Indicate Avoidance) and EPRCA(Enhanced Proportional Rate Control Algorithm) switches which use Explicit Rate switch algorithm for ABR switch. The variation of the ACR at the source end system, the queue length, the utilization rate of the link bandwidth and the share fairness at the transient and steady states are used as the evaluation criteria for the simulation. As a result of simulation, ERICA algorithm switch was ten times long compared to ERPCA switch to achieve assigned fair share. so EPRCA switch is superior to ERICA about load response. For Fair share and stability, ERICA switch is excellent to EPRCA switch.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.643-651
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• 2021

Most people acquire information visually. Screens of computers, smart phones, etc. constantly stimulate people's eyes, increasing fatigue. In this social phenomenon, the realistic and rich sound of the 21st century's state-of-art sound system can affect people's bodies and minds in various ways. Through sound, human beings are given space to calm and observe themselves. The purpose of this paper is to introduce immersive yoga training based on 3D sound conducted together by ALgruppe & Rory's PranaLab and to promote the understanding of immersive audio system. As a result, people, experienced immersive yoga, not only enjoy the effect of sound, but also receive a powerful energy that gives them a sense of inner self-awareness. This is a response to multidisciplinary exchange required by the knowledge of modern society, and at the same time, informs the possibility of new cultural contents.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.439-451
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• 2021

We propose a deep learning-based beamformer combined with spectral subtraction for continuous speech recognition operating in noisy environments. Conventional beamforming systems were mostly evaluated by using pre-segmented audio signals which were typically generated by mixing speech and noise continuously on a computer. However, since speech utterances are sparsely uttered along the time axis in real environments, conventional beamforming systems degrade in case when noise-only signals without speech are input. To alleviate this drawback, we combine online beamforming algorithm and spectral subtraction. We construct a Continuous Speech Enhancement (CSE) evaluation set to evaluate the online beamforming algorithm in noisy environments. The evaluation set is built by mixing sparsely-occurring speech utterances of the CHiME3 evaluation set and continuously-played CHiME3 background noise and background music of MUSDB. Using a Kaldi-based toolkit and Google web speech recognizer as a speech recognition back-end, we confirm that the proposed online beamforming algorithm with spectral subtraction shows better performance than the baseline online algorithm.

• Journal of the Korea Society for Simulation
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• v.30 no.4
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• pp.1-8
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• 2021

Deep learning is one of the most widely accepted methods for the forecasting of time series data which have the complexity and non-linear behavior. In this paper, we investigate the modification of a state-of-art WaveNet deep learning architecture and walk forward validation (WFV) in order to forecast electric power consumption data 24-hour-ahead. WaveNet originally designed for raw audio uses 1D dilated causal convolution for long-term information. First of all, we propose a modified version of WaveNet which activates real numbers instead of coded integers. Second, this paper provides with the training process with tuning of major hyper-parameters (i.e., input length, batch size, number of WaveNet blocks, dilation rates, and learning rate scheduler). Finally, performance evaluation results show that the prediction methodology based on WFV performs better than on the traditional holdout validation.

• The Journal of the Acoustical Society of Korea
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• v.42 no.3
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• pp.214-220
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• 2023

In this paper, we propose a method to improve texture recognition performance from haptic acceleration signals representing the texture characteristics of object surface materials by using a Conformer model that combines the advantages of a convolutional neural network and a transformer. In the proposed method, three-axis acceleration signals generated by impact sound and vibration are combined into one-dimensional acceleration data while a person contacts the surface of the object materials using a tool such as a stylus , and the logarithmic Mel-spectrogram is extracted from the haptic acceleration signal similar to the audio signal. Then, Conformer is applied to the extracted the logarithmic Mel-spectrogram to learn main local and global frequency features in recognizing the texture of various object materials. Experiments on the Lehrstuhl für Medientechnik (LMT) haptic texture dataset consisting of 60 materials to evaluate the performance of the proposed model showed that the proposed method can effectively recognize the texture of the object surface material better than the existing methods.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.257-269
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• 2023

There is currently a burgeoning demand for image synthesis from photos and videos using deep learning models. Existing video synthesis models solely extract motion information from the provided video to generate animation effects on photos. However, these synthesis models encounter challenges in achieving accurate lip synchronization with the audio and maintaining the image quality of the synthesized output. To tackle these issues, this paper introduces a novel framework based on an image animation approach. Within this framework, upon receiving a photo, a video, and audio input, it produces an output that not only retains the unique characteristics of the individuals in the photo but also synchronizes their movements with the provided video, achieving lip synchronization with the audio. Furthermore, a super-resolution model is employed to enhance the quality and resolution of the synthesized output.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.573-578
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• 2008

Recently, we should control various devices such as TV, audio, DVD player, video player, and set-top box simultaneously to manipulate home theater system. To execute the function the user want in this situation, user should know functions and positions of the buttons in several remote controllers. Normally, people feel difficult due to these realistic problems. Besides, the number of the devices that we can control shall increase, and people will confuse more if the ubiquitous home environment is realized. Therefore, user adaptive interface that provides the summarized functions is required. Moreover there can be a lot of mobile and stationary controller devices in ubiquitous computing environment, so user interface should be adaptive in selecting the functions that user wants and in adjusting the features of UI to fit in specific controller. To implement the user and controller adaptive interface, we modeled the ubiquitous home environment and used modeled context and device information. We have used Bayesian network to get the degree of necessity in each situation. Behavior selection network uses predicted user situation and the degree of necessity, and it selects necessary functions in current situation. Selected functions are used to construct adaptive interface for each controller using presentation template. For experiments, we have implemented ubiquitous home environment and generated controller usage log in this environment. We have confirmed the BN predicted user requirements effectively as evaluating the inferred results of controller necessity based on generated scenario. Finally, comparing the adaptive home UI with the fixed one to 14 subjects, we confirmed that the generated adaptive UI was more useful for general tasks than fixed UI.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.167-176
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• 2005

This paper proposes a new power minimization technique for the frame-based multimedia signal processing. The derivation of the technique is based on the newly proposed microscopic DVS(Dynamic Voltage Scaling) method, where, the operating frequency and the supply voltage levels are dynamically controlled according to the processing requirement for each frame of multimedia data. The multimedia signal processing algorithms are also redesigned and optimized to maximize the power saving efficiency of the microscopic DVS technology. The characterization of the mean/variance distribution of the processing load in the frame-based multimedia signal processing provides the major basis not only for the optimized application of the microscopic DVS technology but also for the optimization of the multimedia algorithms. The power saying efficiency of the proposed DVS approach is experimentally tested with the algorithms of MPEG-2 video decoder and MPEG-2 AAC audio encoder on the ARM9 RISC processor. The experimental results with the diverse MPEG-2 video and audio files show The average power saving efficiencies of 50$\%$ and 30$\%$, respectively. The results also agree very well with those of the analytic derivations.