• 한국시뮬레이션학회논문지
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• 제9권3호
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• pp.65-75
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• 2000

In recent years, significant advances in computers and communication technologies have made multimedia services feasible. As a result, various queuing models and cost models on architecture and data placement for multimedia server have been proposed. However, these analytical techniques use only probabilistic models to represent the behavior of a system, and then they have several limitations like accuracy. Simulation is a viable alternative to analytical model. It avoids many of the limitations associated with analytical techniques, allowing for more precise representation of system attributes like workload in program code. In this paper, we propose a simulation test bed that can evaluate performance of real-time multimedia server by using simulation model.

• 한국정보통신학회논문지
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• 제3권1호
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• pp.197-208
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• 1999

본 논문에서는 영상회의를 위한 멀티미디어 하드웨어 플랫폼의 하드웨어 구조를 입출력 시스템 중심으로 제안하고, 그 구조를 대기모델로 표현하여 입출력 시스템의 동작을 분석하였으며, 영상회의 시스템의 구현을 통해 분석결과를 고찰하였다. 영상회의시에 발생되는 멀티미디어 데이타의 병목현상과 비디오 데이타의 크기, 프레임 수, 화자의 수 및 압축율의 변화에 따른 프레임의 대기 시간을 모의실험하여 실현 가능한 영상회의 수준과 문제점을 분석하였다 또 분석된 내용의 요구를 근사적으로 반영하는 입출력 시스템을 구현하고 시험하여 멀티미디어 시스템 입출력 설계시에 고려해야 할 사항들을 기술하였다.

• 한국정보처리학회논문지
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• 제3권3호
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• pp.608-616
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• 1996

본 논문에서는 영상회의를 위한 멀티미디어 하드웨어 구조를 입 출력 중심으로 제안 하고, 구조를 대기모델로 표현하여 시스템의 동작을 분석하였으며, 설계와구현 을 통해 분석결과를 고찰하였다. 영상회의시에 발생되는 멀티미디어 데이타의 병목 현상 과 비디오 데이타의 크기, 프레임 수, 화자의 수 및 압축율의 변화를 모의실험하여 가능한 영상회의 수준과 문제점을 분석하였다. 또 분석된 내용의 요구를 .근사적으로 반영하는 시스팀을 구현하고 시험하여 멀티미디어 시스팀 입축력 설계시에 고려해야 할 사항들을 기술하였다.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1587-1596
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• 2016

This paper presents an interactive locomotion controller using motion capture data and inverted pendulum model. Most of the data-driven character controller using motion capture data have two kinds of limitation. First, it needs many example motion capture data to generate realistic motion. Second, it is difficult to make natural-looking motion when characters navigate dynamic terrain. In this paper, we present a technique that uses dimension reduction technique to motion capture data together with the Gaussian process dynamical model (GPDM), and interpolates the low-dimensional data to make final motion. With the low-dimensional data, we can make realistic walking motion with few example motion capture data. In addition, we apply the inverted pendulum model (IPM) to calculate the root trajectory considering the real-time user input upon the dynamic terrain. Our method can be used in game, virtual training, and many real-time applications.

• 한국멀티미디어학회논문지
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• 제13권12호
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• pp.1814-1819
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• 2010

Since 1987, when statistical analyzing guide for thermal life test of Accelerated Life Test(ALT) was proposed as ANSI/IEEE Std 101, this guide has been used widely for many experiment data. Shim(2004) had done Monte Carlo simulation to compare life of two different systems or materials, based on statistic values obtained from ANSI/IEEE Std 101 data. In this study, a profile analysis is proposed for comparing life of two different systems or materials, and some examples using pre-existing data are given.

• 한국멀티미디어학회논문지
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• 제21권2호
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• pp.271-280
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• 2018

Recently, big data has been growing rapidly due to the development of IT technology. Especially in the medical field, big data is utilized to provide services such as patient-customized medical care, disease management and disease prediction. In Korea, 'National Health Alarm Service' is provided by National Health Insurance Corporation. However, the prediction model has a problem of short-term prediction within 3 days and unreliability of social data used in prediction model. In order to solve these problems, this paper proposes a disease prediction model using medicine prescription data generated from actual patients. This model predicts the total number of patients and the risk of disease in each region and uses the ARIMA model for long-term predictions.

• 한국멀티미디어학회논문지
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• 제24권2호
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• pp.274-284
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• 2021

Customized services to a sleep induction for better sleepcare are more effective because of different satisfaction levels to users. The EOG data measured at the frontal lobe when a person blinks his eyes can be used as biometric data because it has different values for each person. The accuracy of measurement is degraded by a noise source, such as toss and turn. Therefore, it is necessary to analyze the noisy data and remove them from normal EOG by filtering. There are low-pass filtering and high-pass filtering as filtering using a frequency band. However, since filtering within a frequency band range is also required for more effective performance, we propose a machine learning model for the filtering of EOG data in this paper as the second filtering method. In addition, optimal values of parameters such as the depth of the hidden layer, the number of nodes of the hidden layer, the activation function, and the dropout were found through experiments, to improve the performance of the machine learning filtering model, and the filtering performance of 95.7% was obtained. Eventually, it is expected that it can be used for effective user identification services by using filtering model for EOG data.

• Journal of Information Technology Applications and Management
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• 제14권4호
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• pp.61-74
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• 2007

In this paper we consider the Digital Multimedia Broadcasting (DMB) Service that starts recently in Korea and gains popularity. DMB makes it possible to watch high quality TV programs while we are in motion. The service provider or the service researcher are interested in the factors that influence the user's choice of new service such as DMB. Understanding the factors make them create the powerful marketing strategies and develop the new service or product that is attractive for users. We therefore find the factors influencing the user's choice of DMB service, and propose a model for analyzing the relationship between the factors and the intention of buying. The model is based on the Technology Acceptance Model (TAM). We extend the TAM by adding factors including functional attributes of DMB service. We survey the significant functional attributes influencing the intention of buying by using the proposed model.

• 한국멀티미디어학회논문지
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• 제9권12호
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• pp.1607-1616
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• 2006

The growing market of multimedia and digital signal processing requires significant data-path portions of SoCs. However, the common models for verification are not suitable for SoCs. A novel model--WGL (Weighted Generalized List) is proposed, which is based on the general-list decomposition of polynomials, with three different weights and manipulation rules introduced to effect node sharing and the canonicity. Timing parameters and operations on them are also considered. Examples show the word-level WGL is the only model to linearly represent the common word-level functions and the bit-level WGL is especially suitable for arithmetic intensive circuits. The model is proved to be a uniform and efficient model for both bit-level and word-level functions. Then Based on the WGL model, a backward-construction logic-verification approach is presented, which reduces time and space complexity for multipliers to polynomial complexity(time complexity is less than $O(n^{3.6})$ and space complexity is less than $O(n^{1.5})$) without hierarchical partitioning. Finally, a construction methodology of word-level polynomials is also presented in order to implement complex high-level verification, which combines order computation and coefficient solving, and adopts an efficient backward approach. The construction complexity is much less than the existing ones, e.g. the construction time for multipliers grows at the power of less than 1.6 in the size of the input word without increasing the maximal space required. The WGL model and the verification methods based on WGL show their theoretical and applicable significance in SoC design.

• 한국멀티미디어학회논문지
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• 제24권7호
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• pp.868-879
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• 2021

PCB (Printed Circuit Board) inspection using a deep learning model requires a large amount of data and storage. When the amount of stored data increases, problems such as learning time and insufficient storage space occur. In this study, the existing object detection model is changed to a continual learning model to enable the recognition and classification of PCB components that are constantly increasing. By changing the structure of the object detection model to a knowledge distillation model, we propose a method that allows knowledge distillation of information on existing classified parts while simultaneously learning information on new components. In classification scenario, the transfer learning model result is 75.9%, and the continual learning model proposed in this study shows 90.7%.