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차영준,김성재 한국통신학회 2010 韓國通信學會論文誌 Vol.35 No.12
This article presents a PDE-based interpolation algorithm to effectively reproduce high resolution imagery. Conventional PDE-based interpolation methods can produce sharp edges without checkerboard effects; however,they are not interpolators but approximators and tend to weaken fine structures. In order to overcome the drawback, a texture enhancement method is suggested as a post-process of PDE-based interpolation methods. The new method rectifies the image by simply incorporating the bilinear interpolation of the weakened texture components and therefore makes the resulting algorithm an interpolator. It has been numerically verified that the new algorithm, called the PDE-based image interpolator (PII), restores sharp edges and enhances texture components satisfactorily. PII outperforms the PDE-based skeleton-texture decomposition (STD) approach. Various numerical examples are shown to verify the claim.
차영준,임종석 대한전자공학회 1995 전자공학회논문지-A Vol.32 No.1
Metal-Metal Matrix(M$^{3}$) layout is a recently proposed layout style which uses minimum amount of poly wires for high speed operation. In this paper we propose a method of generating functional modules in M$^{3}$ layout style. In the proposed method the transistors and the input/output lines of the given circuit are first placed in M$^{3}$ layout style and then they are interconnected using two metal layers. We develop a new placement method by simulated annealing, and we modify the well known channel routing method for the interconnections. When we applied our method to several logic circuits, the area of the generated layout is smaller than the ones by the previously known method. Our results also compares favorably to the other layout styles like gate matrix layout.
차영준,이학준,정용규 국제문화기술진흥원 2016 The Journal of the Convergence on Culture Technolo Vol.2 No.1
최근 정보통신기술의 발달로 인한 각종 모바일 기기와 스마트 기기를 통해 소셜 네트워크 서비스가 많이 대 중화 되고 있다. SNS는 오프라인에 존재하는 사회적 관계망이 온라인으로 이동한 친목기반 인맥 형성 서비스이다. SNS는 온라인 커뮤니티와 혼동되어 사용되기도 하지만 차이점이 있다. 이러한 기기들로부터 수집된 정보를 모델링 하는 알고리즘으로는 연관성, 군집화, 신경망, 결정 나무 등의 다양한 기법이 제안되고 있다. 이러한 기법들을 활용하 여 여러 가지 방대한 자료를 효과적으로 사용 하는데 연구할 필요가 있다. 따라서 본 논문에서는 특히 군집화에서 좋 은 성능으로 평가받는 EM 알고리즘에 대해서 페이스북 인사이트 데이터를 이용하여 군집화를 수행한 결과를 기반으 로 알고리즘의 성능을 평가하였다. 이를 통하여 EM알고리즘에 따른 성능의 변화와 남호주 주립도서관 의 실험데이 터의 적용결과를 기반으로 분석하였다. As information technologies are rapidly developed recently, social networking services through a variety of mobile devices and smart screen is becoming popular. SNS is a social networking based services which is online forms from existed offline. SNS can also be used differently which is confused with the online community. A modelling algorithm is a variety of techniques, which are assocoation, clustering, neural networks, and decision trees, etc. By utilizing this technique, it is necessary to study to effectively using the large number of materials. In this paper, we evaluate in particular the performance of the algorithm based on the results of the clustering using Facebook Insights data for the EM algorithm to be evaluated as a good performance in clustering. Through this analysis it was based on the results of the application of the experimental data of the change and the South Australian state library according to the performance of the EM algorithm.