• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.403-405
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• 2012

본 연구에서는 인간과 서비스 로봇과의 상호작용에 필요한 동작의 학습을 위한 방법으로 모방학습을 활용한다. 로봇을 모방학습 시키기 위해서는 모방학습을 위한 특정한 구조가 필요하다. 따라서 선행자가 로봇을 직접 움직여 생성한 모방학습 데이터를 저장하고, 그 데이터를 학습알고리즘에 적용시킨 뒤 로봇이 학습 내용을 수행하도록 하는 모방학습 프레임워크를 제안한다. 모방학습 프레임워크의 프로그래밍은 본 연구에서 사용하는 휴머노이드 로봇인 나오에서 제공하는 그래픽기반 환경 개발도구인 콜레그래프를 활용한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.249-251
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• 2021

본 논문에서는 Photon Unity Network[1]를 사용하여 멀티플레이 VR게임 개발 방법을 제안한다. Unity 3D와 Oculus Framework를 활용하여 플레이어 기능을 구현했다. 그리고 Photon Unity Network를 이용하여 서버와 여러 명의 플레이어를 연결해 줄 수 있다.

• Journal of Information Processing Systems
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• v.5 no.1
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• pp.19-24
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• 2009

Many researchers have developed frameworks that are capable of handling context information and can be adapted and used by any Web service. However, no research involving the systematic analysis of existing frameworks has yet been conducted. This paper examines the Context Framework, an example of existing frameworks, using a Petri net, and analyzes its advantages and disadvantages. Then, a Petri net model - with its disadvantages removed - is introduced, and a new framework is presented on the basis of that model. The proposed PAWS (Privacy Aware Web Services) framework has a expendability for context management and communicates flexible context information for every session. The proposed framework can solve overhead problems of context in SOAP messages. It also protects user privacy according to user preferences.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1491-1494
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• 2003

Video adaptation in response to dynamic resource conditions and user preferences is required as a key technology to enable universal multimedia access (UMA) through heterogeneous networks by a multitude of devices in a seamless way. Although many adaptation techniques exist, selections of appropriate adaptations among multiple choices are often ad hoc. To provide a systematic solution, we present a general conceptual framework to model video entity, adaptation, resource, utility, and relations among them. It allows for formulation of various adaptation problems as resource-constrained utility maximization. We apply the framework to a practical case of dynamic bit rate adaptation. Furthermore, we present a description tool, which has been accepted as a part of the MPEG-21 Digital Item Adaptation (DIA), along with a brief overview of the .elated descriptors to support terminal and network quality of service (QoS).

• ETRI Journal
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• v.36 no.2
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• pp.197-205
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• 2014

This paper proposes a novel framework for virtual content delivery networks (CDNs) based on cloud computing. The proposed framework aims to provide multimedia content delivery services customized for content providers by sharing virtual machines (VMs) in the Infrastructure-as-a-Service cloud, while fulfilling the service level agreement. Furthermore, it supports elastic virtual CDN services, which enables the capabilities of VMs to be scaled to encompass the dynamically changing resource demand of the aggregated virtual CDN services. For this, we provide the system architecture and relevant operations for the virtual CDNs and evaluate the performance based on a simulation.

• Journal of Multimedia Information System
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• v.7 no.1
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• pp.73-86
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• 2020

The well-known sentence, "You can't manage what you don't measure" suggests the importance of measurement. The Ministry of National Defense (MND) in Korea is measuring the effort of informatization for various dimensions such as validity, adequacy, and effectiveness using the MND evaluation system to obtain positive and significant effects from informatization. MND views the defense informatization domain as divided into the defense informatization policy, the defense informatization project, and the defense informatization level, which can measure the informatization capability of the MND and the armed forces or organizations. Furthermore, it feels there is some limitation, such as those related to ambiguity and reliability, present in the system. To overcome the limitations in the existing system to evaluate the defense informatization policy, this study proposes a revised evaluation framework for the policy of defense informatization, its indicators, and measurement methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.178-183
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• 2009

Online image dictionary has become more and more popular in concepts cognition. However, for existing online systems, only very few images are manually picked to demonstrate the concepts. Currently, there is very little research found on automatically choosing large scale online images with the help of semantic analysis. In this paper, we propose a novel framework to utilize community-generated online multimedia content to visually illustrate certain concepts. Our proposed framework adapts various techniques, including the correlation analysis, semantic and visual clustering to produce sets of high quality, precise, diverse and representative images to visually translate a given concept. To make the best use of our results, a user interface is deployed, which displays the representative images according the latent semantic coherence. The objective and subjective evaluations show the feasibility and effectiveness of our approach.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1403-1413
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• 2021

In this paper, we investigate automated data validation techniques for artificial intelligence training, and also disclose open-source frameworks, such as Google's TensorFlow Data Validation (TFDV), that support automated data validation in the AI model development process. We also introduce an experimental study using public data sets to demonstrate the effectiveness of the open-source data validation framework. In particular, we presents experimental results of the data validation functions for schema testing and discuss the limitations of the current open-source frameworks for semantic data. Last, we introduce the latest studies for the semantic data validation using machine learning techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.385-405
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• 2019

High Efficiency Video Coding (HEVC) enables significantly improved compression performance relative to existing standards. However, the advance also requires high computational complexity. To accelerate the intra prediction mode decision, a minimum risk Bayesian classification framework is introduced. The classifier selects a small number of candidate modes to be evaluated by a rate-distortion optimization process using the sum of absolute Hadamard transformed difference (SATD). Moreover, the proposed method provides a loss factor that is a good trade-off model between computational complexity and coding efficiency. Experimental results show that the proposed method achieves a 31.54% average reduction in the encoding run time with a negligible coding loss of 0.93% BD-rate relative to HEVC test model 16.6 for the Intra_Main common test condition.

• Journal of Korea Game Society
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• v.18 no.4
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• pp.5-14
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• 2018

Nowadays, game development of new genres continues through convergence among existing genres, and the games of this hybrid-genre are gaining popularity around the world. Following this trend, it is meaningful to analyze the characteristic contents of the existing genre for more effective genre fusion. In this paper, in the genre of survival game, a genre of digital game, we would like to select a representative survival game for analysis of survival content, which is a key goal and core of the game, to identify common and differentiated features. For this purpose, we have studied game mechanics and game dynamic components around the contents of the survival game, based on the MDA framework.