• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.837-840
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• 2005

This paper presents 3D graphics lighting processor based on vector processing using pipeline chaining. The lighting process of 3D graphics rendering contains many arithmetic operations and its complexity is very high. For high throughput, proposed processor uses pipelined functional units. To implement fully pipelined architecture, we have to use many functional units. Hence, the number of functional units is restricted. However, with the restricted number of pipelined functional units, the utilization of the units is reduced and a resource reservation problem is caused. To resolve these problems, the proposed architecture uses vector processing using pipeline chaining. Due to its pipeline chaining based architecture, it can perform 4.09M vertices per 1 second with 100MHz frequency. The proposed 3D graphics lighting processor is compatible with OpenGL ES API and the design is implemented and verified on FPGA.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.169-178
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• 2019

Due to the characteristics of an ad hoc network without a control center, self-organization, and flexible topology, the trust evaluation of the nodes in the network is extremely difficult. Based on the analysis of ad hoc networks and the blockchain technology, a blockchain-based node-level trust evaluation model is proposed. The concepts of the node trust degree of the HASH list on the blockchain and the perfect reward and punishment mechanism are adopted to construct the node trust evaluation model of the ad hoc network. According to the needs of different applications the network security level can be dynamically adjusted through changes in the trust threshold. The simulation experiments demonstrate that ad-hoc on-demand distance vector(AODV) Routing protocol based on this model of multicast-AODV(MAODV) routing protocol shows a significant improvement in security compared with the traditional AODV and on-demand multipath distance vector(AOMDV) routing protocols.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.46-55
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• 2020

Ad Hoc network is a special wireless network, mainly because the nodes are no control center, the topology is flexible, and the networking could be established quickly, which results the transmission stability is lower than other types of networks. In order to guarantee the transmission of data packets in the network effectively, an improved Queue Ad Hoc On-demand Distance Vector Routing protocol (Q-AODV) for node detection by using blockchain technology is proposed. In the route search process. Firstly, according to the node's daily communication record the cluster is formed by the source node using the smart contract and gradually extends to the path detection. Then the best optional path nodes are chained in the form of Merkle tree. Finally, the best path is chosen on the blockchain. Simulation experiments show that the stability of Q-AODV protocol is higher than the AODV protocol or the Dynamic Source Routing (DSR) protocol.

• Annual Conference on Human and Language Technology
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• 2003.10d
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• pp.7-13
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• 2003

인터넷을 통해 생성, 전달되는 문서 량이 급격히 많아짐에 따라, 정보의 접근을 용이하게 하기 위한 문서의 자동 분류 기능이 절실히 요구되고 있다. SVM(Support Vector Machine)은 최근에 문서 분류에 널리 쓰이고 있는 기법으로 다른 분류기에 비하여 좋은 성능을 보여주고 있다. 하지만 SVM은 현재까지 주로 비 계층 평탄화(flat)된 분류 응용에 효과적으로 적용되어 왔다. 이와 달리 본 논문은 문서 분류에 있어서 최종 분류 class를 한번에 출력하는 비 계층 분류보다는, 비슷한 성질을 갖는 class의 집합을 계층적 구조로 묶어 분류하는 계층적 분류 기법이 보다 사람이 이해하기 쉽고 사용하기 편리하며 더 효과적이라는 것을 보이고, 실험을 통해 계층적 분류를 위한 효과적인 SVM분류기를 개발하여 비 계층 분류보다 좋은 분류 성능을 보여 줄 수 있음을 확인한다.

• ETRI Journal
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• v.30 no.2
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• pp.335-337
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• 2008

An eye detection method for facial images using Zernike moments with a support vector machine (SVM) is proposed. Eye/non-eye patterns are represented in terms of the magnitude of Zernike moments and then classified by the SVM. Due to the rotation-invariant characteristics of the magnitude of Zernike moments, the method is robust against rotation, which is demonstrated using rotated images from the ORL database. Experiments with TV drama videos showed that the proposed method achieved a 94.6% detection rate, which is a higher performance level than that achievable by the method that uses gray values with an SVM.

• Journal of Korea Game Society
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• v.5 no.1
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• pp.19-24
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• 2005

To get the realistic deformation of fractal objects in computer games, fractal-like deformation property should be added to ordinary continuous deformations. We, here, suggest a fractal-like vector fields producing method using the code and its modification, and some examples are given.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.240-245
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• 2006

본 논문에서는 의상에 대한 사용자 선호도를 찾아내는 기법에 대하여 기술한다. 의상에 대한 사용자 선호도를 찾기 위해서 의상 데이터에 대해 데이터 모델을 새롭게 제안한다. 이 데이터 모델을 기반으로 사용자의 의상관련 히스토리를 저장한다. 이렇게 저장된 히스토리 정보에 기계 학습 기법 중 최근 각광받고 있는 SVM 기법을 적용하여 사용자 선호도를 찾아내도록 하였다. 이 결과를 다른 학습 기법인 Naive Bayes 기법을 사용하여 의상에 대한 사용자 선호도를 검색한 성능과 비교하여 우리 모델이 더 좋다는 것을 확인하였다. 우리는 5명의 사용자에 대해서 동일한 취향을 갖는 사용자가 몇 명인지에 따라 A(모두 다름), B(2명), C(3명), D(4명), E(모두 같음) 형태별, 사용자별 1000건의 히스토리를 일정한 기준에 따라 생성했다. 그리고 이 중에서 900건을 학습용 데이터, 100건을 검증용 데이터로 선정하여 실험이 진행되었다.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.351-361
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• 2010

The solution of large sparse linear systems is one of the most important problems in large scale scientific computing. Among the many methods developed, the preconditioned Krylov subspace methods are considered the preferred methods. Selecting a suitable preconditioner with appropriate parameters for a specific sparse linear system presents a challenging task for many application scientists and engineers who have little knowledge of preconditioned iterative methods. The prediction of ILU type preconditioners was considered in [27] where support vector machine(SVM), as a data mining technique, is used to classify large sparse linear systems and predict best preconditioners. In this paper, we apply the data mining approach to the sparse approximate inverse(SAI) type preconditioners to find some parameters with which the preconditioned Krylov subspace method on the linear systems shows best performance.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1138-1145
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• 2013

A novel predictive current control strategy for a sparse matrix converter is presented. The sparse matrix converter is functionally-equivalent to the direct matrix converter but has a reduced number of switches. The predictive current control uses a model of the system to predict the future value of the load current and generates the reference voltage vector that minimizes a given cost function so that space vector modulation is achieved. The results show that the proposed controller for sparse matrix converters controls the load current very effectively and performs very well through simulation and experimental results.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.217-227
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• 2017

Crosswalk detection is an important part of the Pedestrian Protection System in autonomous vehicles. Different methods of crosswalk detection have been introduced so far using crosswalk edge features, the distance between crosswalk blocks, laser scanning, Hough Transformation, and Fourier Transformation. However, most of these methods failed to detect crosswalks accurately, when they are damaged, faded away or partly occluded. Furthermore, these methods face difficulties when applying on real road environment where there are lot of vehicles. In this paper, we solve this problem by first using a region based binarization technique and x-axis histogram to detect the candidate crosswalk areas. Then, we apply Support Vector Machine (SVM) based classification method to decide whether the candidate areas contain a crosswalk or not. Experiment results prove that our method can detect crosswalks in different environment conditions with higher recognition rate even they are faded away or partly occluded.