• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.3
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• pp.180-187
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• 2014

This paper introduces reliable multicast MAC protocol for cooperative unmanned vehicles. cooperative unmanned vehicles communicate with infrastructure and other unmanned vehicles in order to increase driving safety. They exchange information related to driving and thus it requires real-time and reliable multicast. However, the international vehicular communication standard, IEEE 802.11p WAVE, does not provide a reliable multicast scheme on the MAC layer. To address the problems of reliability, we propose a reliable multicast protocol called WiVCL, which avoids contention and collision. Our evaluation shows that the WiVCL achieves a high degree of reliability and real-time features.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.5
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• pp.513-527
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• 2000

This paper describes our experience to design and implementation of a collaborative system framework that allows to develop certain collaborative applications such as 3D animation, computer game, and industrial design. The collaborative system enables users, who located in geographically long distance, to do collaborative work in a single virtual space. The proposed system basically consists of client and server system. The goal of proposed system is to support scalability, portability, and platform independent. In order to achieve these, the server is implemented in Java platform and is adopted to the hybrid architecture which takes the advantages both in centralized and decentralized collaborative system. We construct the server base on its functional characteristics so called User Manager Server (UMS), Session Manager Server (SMS), and Information Server (IS), The UMS manages the users who are taking part in the collaborative operations. The SMS supports the conferencing in the proposed system. The IS provides the connection methods among the UMSs. For user's convenience, we implement the client using Visual C++ in Windows. We also expend the functions of 3D Studio Max to distributed environment by means of the plug-in module, and facilitate the chatting and white board functions as well.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.6
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• pp.39-47
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• 2012

As a scheme to efficiently reduce the effects of multipath fading in next generation wireless communication systems, cooperative communication systems have recently come into the spotlight. Since these cooperative communication systems use cooperative relays with diverse fading coefficients to transmit information, having all relays participate in cooperative communication may result in unnecessary waste of resources, and thus relay selection schemes are required to efficiently use wireless resources. In this paper, we propose an efficient relay selection scheme through self-learning in cooperative wireless networks using Q-learning algorithm. In this scheme, we define states, actions and two rewards to achieve good SER (Symbol Error Rate) performance, while selecting a small number of cooperative relays. When these parameters are well-defined, we can obtain good performance. For demonstrating the superiority of the proposed Q-learning, We compared the proposed scheme with Q-learning and a relay selection scheme with a mathematical analysis. The simulation results show that, compared to a scheme that obtains optimum relays through a mathematical analysis, the proposed scheme uses resources efficiently by using smaller numbers of relays with comparable SER performance. According to these simulation results, the proposed scheme can be considered as a good attempt for future wireless communication.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.607-609
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• 2005

온라인 및 오프라인 상에서 추천시스템에 대한 요구가 커지고 있으며 이에 관련해 않은 연구가 이루어지고 있다. 추천시스템은 마케팅 활용의 관점에서 목표 상품에 대한 반응 가능성이 높은 고객군을 추천하는 타겟마케팅 추천시스템과 고객 개인별로 구매 가능성이 높은 상품을 추천하는 개인화 추천시스템으로 구분할 수 있다. 지금까지의 추천시스템에 관한 연구는 대부분 개인화 추천시스템의 효율 향상에 목표를 두고 있다. 그러나 기업의 타겟마케팅에 대한 요구를 적절히 지원하지 못하고 있어 타겟마케팅에 대한 연구가 필요하다. 본 연구에서는 상품별 구매 패턴을 이용하는 프로파일 기반 추천 방법을 제안하고 이 방법과 기존의 협력적 추천 방법을 결합하여 특정 상품에 반응 가능성이 높은 고객을 추천하는 방법을 제안한다. 프로파일 기반 추천에서는 카이스퀘어 검정을 사용하여 상품별로 구매 패턴에 영향을 미치는 요인을 추출하고 이를 이용하여 특징 고객군을 선별하여 전체 고객군과 특징 고객과의 엔트로피(Entropy)의 변이 정도를 예측값으로 사용한다. 실험결과, 프로파일 기반 추천과 협력적 추천을 결합하여 추천하는 방법은 한 가지 방법을 사용할 때 보다 좋은 추천 정확도를 나타내었다.

• Journal of the Korean association of regional geographers
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• v.21 no.4
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• pp.631-638
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• 2015

The aim of this article is to analyze problems of the government-led region-based business-university-research institute collaborations(BURIC) in Korea and to present main issues for solving and improving the current 'cul-de-sac' of these collaborations. The main problem of such collaborations is the wider divergence of opinions by actors who implement projects of the BURIC funded by the central and local government. Due to this problem, each region, mainly the non-Seoul metropolitan region, in Korea has problems of the system and people for BURIC. Within this context, main issues of the government-led and region-based BURIC is focused upon BURIC for the start-up of self-employment and the expansion of companies' lifespan. Since 2000, experts and policy-makers have emphasized business- (or company-) centered BURIC rather than University-focused one. This point of view should be improved or corrected. That is to say, policies of BURIC are in need of focusing upon the start-up for self-employment and the expansion of companies' lifespan.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.5
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• pp.541-550
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• 2003

It is important for the strategy of product sales to investigate the consumer's sensitivity and preference degree in the environment that the process of material development has been changed focusing on the consumer renter. In the present study, we propose the Fashion Design Recommender System (FDRS) of textile design applying collaborative filtering personalization technique as one of methods in the material development centered on consumer's sensibility and preferences. In collaborative filtering personalization technique based on textile, Pearson Correlation Coefficient is used to calculate similarity weights between users. We build the database founded on the sensibility adjective to develop textile designs by extracting the representative sensibility adjective from users' sensibility and preferences about textile designs. FDRS recommends textile designs to a consumer who has a similar propensity about textile. Ultimately, this paper sugeests empirical applications to verify the adequacy and the validity on this system with the development of Fashion Design Recommender System (FDRS)

• Journal of Convergence for Information Technology
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• v.9 no.5
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• pp.27-33
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• 2019

Various technical and societal approaches are being made to realize the auto driving (AD) and cooperative driving (CD) including communication network and extended advanced driver support system is under development. In CD, it is important to share the roles of the driver and the system and to secure the stability of the driving, so a efficient interface scheme between the driver and the vehicle is required. This study proposes a research model including driver, system and driving environment considering the role and function of driver and system in CD. An efficient interface between the driver and the vehicle to cope with various driving situations on the CD using the analysis of the driving environment and the research model is also proposed. Through this study, it is expected that the proposed research model and interface scheme could contribute to CD system design, cockpit module development and interface device development.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.332-342
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• 2004

With the explosive growth of information in our real life, information filtering is quickly becoming a popular technique for reducing information overload. Information filtering technique is divided into two categories: content-based filtering and collaborative filtering (or social filtering). Content-based filtering selects the information based on contents; while collaborative filtering combines the opinions of other persons to make a prediction for the target user. In this paper, we describe a new filtering approach that seamlessly combines content-based filtering and collaborative filtering to take advantages from both of them, where a technique using user profiles efficiently on the collaborative filtering framework is introduced to predict a user's preference. The proposed approach is experimentally evaluated and compared to conventional filtering. Our experiments showed that the proposed approach not only achieved significant improvement in prediction quality, but also dealt with new users well.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.287-293
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• 2013

Cognitive radio has been recently proposed to dynamically access unused-spectrum. The CR users can share the same frequency band with the primary user without interference to each other. Usually each CR user needs to determine spectrum availability by itself depending only on its local observations. But uncertainty communication environment effects can be mitigated so that the detection probability is improved in a heavily shadowed environment. Soft detection is a primary user detection method of cooperative cognitive radio networks. In our research, we will improve system detection probability by using optimal cooperative node selection algorithm. New algorithm can find optimal number of cooperative sensing nodes for cooperative soft detection by using maximum ratio combining (MRC) method. Through analysis, proposed cooperative node selection algorithm can select optimal node for cooperative sensing according to the system requirement and improve the system detection probability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2C
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• pp.229-237
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• 2010

The conventional detection methods developed for spatially-multiplexed MIMO systems such as OSIC and QRD-M show performance difference for each user depending on the order of detection when they are applied to detection of multi-user signals in uplink multiuser systems based on collaborative spatial multiplexing. In this paper, a signal detection method for uplink multiuser systems based on collaborative spatial multiplexing is proposed to provide similar performance for each user while its performance is close to the case of ML detection. Compared with QRD-M method, computational complexity of the proposed signal detection method is similar in the case of QPSK, and significantly lower in the case of high modulation order with 16-QAM and 64-QAM.