• Journal of Digital Convergence
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• v.16 no.6
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• pp.449-462
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• 2018

The purpose of this study is to develop a competency-based convergence curriculum for the development of sports marketers, sports talent in the sports industry. For this purpose, we conducted literature analysis, in-depth interviews and job analysis to derive necessary capabilities to become sports marketers, draw up a capability profile, and then developed a capability model through expert verification. Sports marketers ' capacity models were divided into sport marketing / PR and sports events by type of experience, with six common basic competencies including sports mind and 12 professional competencies including sponsorships. Sports marketers education courses developed based on capacity models are composed of understanding of sports industry, sports marketing communication, sports law, understanding of sports facility, sports facilities management, sports sponsorship, sports media, sports licensing, sports agent, sports event planning, sports event management, make a proposal, sports event field practice. The developed training courses for sports marketers will be used in colleges and private education institutions related to the sports industry, contributing to fostering and expanding sports industry talent.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.237-246
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• 2008

According to the development of information & web technology and the amount of information increases, there have been numerous problems exposed. Although, software engineers try to overcome the limitations by using software agent and web service, there hasn't been satisfactory result in the paradigm of current software agent being a provider to the user's demand. Moreover, the latest configuration of software development is based on CBD (Component Based Development). However, to construct new component using CBD costs great deal of expenses and therefore, a new model which can acquirecomponent information on the web promptly and accurately with low expenses is required. In this paper, the repository management system which acquires and manages on the Semantic web is designed and compare them to the existing component repository management and present its analysis result. In addition, to overcome the limitations of existing component repository system; low accuracy of search result, restrictive search vocabulary and faulty information, the specific plan is presented to perform a knowledge search for the component.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.1-13
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• 2004

This paper presents a method for the multilingual product retrieval agent through XML and the semantic networks in e-commerce. Retrieval for products is an important process, since it represents interfaces of the customer contact to the e-commerce. Keyword-based retrieval is efficient as long as the product information is structured and organized. But when the product information is expressed across many online shopping malls, especially when it is expressed in different languages with cultural backgrounds, buyers' product retrieval needs language translation with ambiguities resolved in a specific context. This paper presents a RDF modeling case that resolves semantic problems in the representation of product information and across the boundaries of language domains. With adoption of UNSPSC code system, this paper designs and implements an architecture for the multilingual product retrieval agents. The architecture is based on the central repository model of product catalog management with distributed updating processes. It also includes the perspectives of buyers and suppliers. And the consistency and version management of product information are controlled by UNSPSC code system. The multilingual product names are resolved by semantic networks, thesaurus and ontology dictionary for product names.

• Journal of Internet Computing and Services
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• v.7 no.3
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• pp.1-11
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• 2006

If a mobile node out of home domain asks to provide mobility service, the mobile should be permitted by the home domain. This can be accomplished by the usage of AAA but the recent studies have shown its weakness to fail the ability of mobile node. This study suggests Fast Handoff model which will shorten permission time by AAA and allow the mobility service to be more efficient. Our suggestion with Assertion function is a new approach to assist authentication capability through mutual authentication of each V_AAA when the distance between HA and itself gets far or its delay time becomes longer. Our suggestion verifies its efficiency by cost analysis.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.2
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• pp.112-123
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• 2005

The latest E-commerce sites provide personalized services to maximize user satisfaction for Internet user The collaborative filtering is an algorithm for personalized item real-time recommendation. Various supplementary methods are provided for improving the accuracy of prediction and performance. It is important to consider these two things simultaneously to implement a useful recommendation system. However, established studies on collaborative filtering technique deal only with the matter of accuracy improvement and overlook the matter of performance. This study considers representative attribute-neighborhood, recommendation textile set, and similarity grouping that are expected to improve performance to the recommendation agent system. Ultimately, this paper suggests empirical applications to verify the adequacy and the validity on this system with the development of Fashion Design Recommendation Agent System (FDRAS ).

• Journal of Korea Multimedia Society
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• v.5 no.1
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• pp.68-76
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• 2002

Multicast in mobile host has the problem of hast mobility, multicast decision, triangle routing, tunnel convergence, implosion of retransmission, and bandwidth waste. In particular, the bandwidth waste in radio is a definite factor that decreases transmission rate. To solve the problems, this paper proposes a new multicast transmission protocol called FIM(Forward Error Correction Integrated Multicast), which supports reliable packet recovery mechanism by integrating If Mobility Support for the host mobility, IGMP(Interned Group Management Protocol) for the group management, and DVMRP(Distance Vector Multicast Routing Protocol) for the multicast routing, and it also uses FEC and the local recovery method based on receiver. The performance measurement is performed by dividing the losses into the homogeneous independent loss, the heterogeneous independent loss, and the shared source link loss model.. The result shows that the performances improves in proportion to the size of local areal group when the size of transmission group exceeds designated size. This indicates FIM is effective in the environment where there are much of data and many receivers in the mobile host.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.932-939
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• 2009

This paper implements the graphic service template authoring tool based on the service template object model of describing the meta information of the services for early childhood education in the semantic web service environment. Our proposed system provides the robot services by constructing web services automatically and making the appropriate service plans. Moreover, it can create, append, delete, and update the service templates of URC based on STDL, and provide the graphic function on service template resources. In order to provide the user friendly environment in the service template phase, we implement the various editing environment : flow view style, grid view style, and text view style. We also provide the easy editing function by realizing abstract service block based on the robot API. Finally we can offer the intelligent and autonomous service of service agent based on semantic information.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.175-181
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• 2021

This paper analyzes the artificial intelligence-based approach for short-term energy consumption prediction. In this paper, we employ the reinforcement learning algorithms to improve the limitation of the supervised learning algorithms which usually utilize to the short-term energy consumption prediction technologies. The supervised learning algorithm-based approaches have high complexity because the approaches require contextual information as well as energy consumption data for sufficient performance. We propose a deep reinforcement learning algorithm based on multi-agent to predict energy consumption only with energy consumption data for improving the complexity of data and learning models. The proposed scheme is simulated using public energy consumption data and confirmed the performance. The proposed scheme can predict a similar value to the actual value except for the outlier data.

• Journal of the Korea Computer Graphics Society
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• v.29 no.4
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• pp.7-16
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• 2023

For decades, creating a desired locomotive motion in a goal-oriented manner has been a challenge in character animation. Data-driven methods using generative models have demonstrated efficient ways of predicting long sequences of motions without the need for explicit conditioning. While these methods produce high-quality long-term motions, they can be limited when it comes to synthesizing motion for challenging novel scenarios, such as punching a random target. A state-of-the-art solution to overcome this limitation is by using a GAN Discriminator to imitate motion data clips and incorporating reinforcement learning to compose goal-oriented motions. In this paper, our research aims to create characters performing combat sports such as boxing, using a novel reward design in conjunction with existing GAN-based approaches. We experimentally demonstrate that both the Adversarial Motion Prior [3] and Adversarial Skill Embeddings [4] methods are capable of generating viable motions for a character punching a random target, even in the absence of mocap data that specifically captures the transition between punching and locomotion. Also, with a single learned policy, multiple task controllers can be constructed through the TimeChamber framework.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.5
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• pp.517-521
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• 2008

A worm is a malware that propagates quickly from host to host without any human intervention. Need of early worm detection has changed research paradigm from signature based worm detection to the behavioral based detection. To increase effectiveness of proposed solution, in this paper we present mechanism of detection and prevention of worm in distributed fashion. Furthermore, to minimize the worm destruction; upon worm detection we propagate the possible attack aleγt to neighboring nodes in secure and organized manner. Considering worm behavior, our proposed mechanism detects worm cycles and infection chains to detect the sudden change in network performance. And our model neither needs to maintain a huge database of signatures nor needs to have too much computing power, that is why it is very light and simple. So, our proposed scheme is suitable for the ubiquitous environment. Simulation results illustrate better detection and prevention which leads to the reduction of infection rate.