• 한국통신학회논문지
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• 제25권10B호
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• pp.1732-1743
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• 2000

In this paper a fixed-delay trellis search with decision feedback (FDTrS/DF) for high-density DVD systems (4.7-15GB) is proposed and implemented with FPGA. The proposed FDTrS/DF is derived by transforming the binary tree search structure into trellis search structure implying that FDTrS/DF performs better than the singnal detection techniques based on tree search structure such as FDTS/DF and SSD/DF. Advantages of FDTrS/DF are significant reductions in hardware complexity due to the unique structure of FDTrS composed of only one trellis stage requiring no traceback procedure usually implemented in the Viterbi detector. Also in this paper the PDFS/DF and SSD/DF orginally proposed for high-density magnetic recording systems are modified for the DVD system and compared with the proposed FDTrS/DF. In order to increase speed in the FPGA implementation the pipelining technique and absolute branch metric (instead of square branch metric) are applied. The proposed FDTrS/DF is shown to provide the best performance among various signal detection techniques such as PRML, DFE, FDTS/DF and SSD/DF even with a small hardware complexity.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2010년도 한국컴퓨터종합학술대회논문집 Vol.37 No.1(C)
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• pp.62-65
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• 2010

Image annotations allow users to access a large image database with textual queries. But since the surrounding text of Web images is generally noisy. an efficient image annotation and retrieval system is highly desired. which requires effective image search techniques. Data mining techniques can be adopted to de-noise and figure out salient terms or phrases from the search results. Clustering algorithms make it possible to represent visual features of images with finite symbols. Annotationbased image search engines can obtains thousands of images for a given query; but their results also consist of visually noise. In this paper. we present a new algorithm Double-Circles that allows a user to remove noise results and characterize more precise representative annotations. We demonstrate our approach on images collected from Flickr image search. Experiments conducted on real Web images show the effectiveness and efficiency of the proposed model.

• 한국컴퓨터정보학회논문지
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• 제24권1호
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• pp.57-65
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• 2019

In this paper, we propose a Rights Management Information(RMI) expression systems for individual sites are integrated and the performance evaluation is performed to find out an efficient comparing and updating method of RMI through various image feature point search techniques. In addition, we proposed a weighted scoring model for both public domain sites and posts in order to use the most latest RMI based on reliable data. To solve problem that most public domain sites are exposed to copyright infringement by providing inconsistent RMI(Rights Management Information) expression system and non-up-to-date RMI information. The weighted scoring model proposed in this paper makes it possible to use the latest RMI for duplicated images that have been verified through the performance evaluation experiments of SIFT and CNN techniques and to improve the accuracy when applied to search engines. In addition, there is an advantage in providing users with accurate original public domain images and their RMI from the search engine even when some modified public domain images are searched by users.

• 한국정밀공학회지
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• 제14권12호
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• pp.24-29
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• 1997

Recently, Genetic Algorithm(GA), which is a stochastic direct search strategy that mimics the process of genetic evolution, is widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA is very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GA. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher porbability of convergence to global optimum compared to traditional techniques which take one-point search method. The methods consist of three genetics opera- tions named selection, crossover and mutation. In this study, a method of finding the omtimum size and topology of drilling machine is proposed by using the GA, For rapid converge to optimum, elitist survival model,roulette wheel selection with limited candidates, and multi-point shuffle cross-over method are adapted. And pseudo object function, which is the combined form of object function and penalty function, is used to include constraints into fitness function. GA shows good results of weight reducing effect and convergency in optimal design of drilling machine.

• International Journal of Naval Architecture and Ocean Engineering
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• 제8권6호
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• pp.602-614
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• 2016

It is necessary to develop an efficient optimization technique to perform optimum designs which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points well by spreading points randomly entire the design spaces. In this paper, Pareto Strategy (PS) multi-objective function method is developed by considering the search direction based on Pareto optimal points, the step size, the convergence limit and the random number generation. The success points between just before and current Pareto optimal points are considered. PS method can also apply to the single objective function problems, and can consider the discrete design variables such as plate thickness, longitudinal space, web height and web space. The optimum design results are compared with existing Random Search (RS) multi-objective function method and Evolutionary Strategy (ES) multi-objective function method by performing the optimum designs of double bottom structure and double hull tanker which have discrete design values. Its superiority and effectiveness are shown by comparing the optimum results with those of RS method and ES method.

• 대한조선학회논문집
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• 제42권2호
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• pp.175-182
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• 2005

It is necessary to develop an efficient optimization technique to optimize the engineering structures which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of engineering structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points by spreading point randomly entire the design spaces. In this paper, a Pareto optimal based multi-objective function method (PMOFM) is developed by considering the search direction based on Pareto optimal points, step size, convergence limit and random search generation . The PMOFM can also apply to the single objective function problems, and can consider the discrete design variables such as discrete plate thickness and discrete stiffener spaces. The design results are compared with existing Evolutionary Strategies (ES) method by performing the design of double bottom structures which have discrete plate thickness and discrete stiffener spaces.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제6권5호
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• pp.487-495
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• 2000

정보 특성 시각화는 기존의 정보 검색 기법과 시각화 기법을 통합하여 방대하고 다양한 인터넷 정보에 대한 이해도를 높임으로써 정보 검색 시 요구되는 시간과 노력을 감소시키며, 검색된 결과에 대한 통계치를 시각적으로 보여줌으로써 검색 결과 중에 정보에 관련된 동향을 파악하는데 유용하다. 전자 도서관의 예에서 볼 수 있듯이 최근 정보 시각화에 관한 관심이 증가하면서 주로 선진국을 중심으로 여러 가지 시각화 기법에 대한 연구와 이를 적용한 검색 시스템들이 개발되고 있다. 따라서 이 논문에서는 정보의 특성을 체계적이며 시각적으로 표현하기 위해, 정보 시각화의 구성 요소를 다양한 뷰를 통해 획일화하고 구조적 정보 분류 기법을 적용한 새로운 차원의 패러다임을 제시하고, 사용자가 보다 쉽게 정보를 항해하고 정보에 대한 이해도를 향상시키기 위한 검색 도구를 개발함으로써 검색 정보에 대한 사용자 이해도와 검색의 효율을 향상시켰다.

• 인터넷정보학회논문지
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• 제11권2호
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• pp.49-60
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• 2010

H.264/AVC 표준은 여러 가지 신기술들을 접목시킴으로써 기존의 동영상 표준들보다 한층 개선된 부호화 효율성을 제공한다.하지만, H.264/AVC 인코더의 향상된 부호화 기술은 그것의 전반적인 복잡도를 크게 증가시켰다. 따라서, 인코더의 복잡도 수준을 경감시키기 위한 최적화의 연구는 중대한 선결 과제이다. 특히, 움직임 추정 부분에 대한 계산량의 비율은 인코더의 작업시간을 크게 좌우한다. 본 논문에서는 완전 다이아몬드와 12각형을 기본 탐색 패턴으로 사용하고 특정한 임계기준치를 적용시킴으로써 효율적으로 정적 블록들을 스킵하는 다이아몬드 웹 격자 탐색 알고리즘을 제안한다. 실험 결과는 본 논문에서 제안된 기법이 기존의 UMHexagonS 알고리즘의 계산량을 12%까지 감소시키면서도 유사한 PSNR을 유지한다는 것을 보여준다.

• 한국정보관리학회:학술대회논문집
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• 한국정보관리학회 1997년도 제4회 학술대회 논문집
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• pp.37-53
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• 1997

The huge size of Internet does not allow ordinary information seekers to search information with ease. Now, it is almost impossible to navigate the ocean of information without effective search tools. Web search engine has been the most effective technology for information retrieval on WWW. But recently, the need for new search tools on WWW or Internet has increased drastically. Currently, there are many on-going researches on the related topics. In this survey, we categorize the new search tools into four types: monitoring systems, filtering systems, browsing assistant systems, recommending systems. These example systems are examined. We are especially interested in WWW information filtering. It is studied how to apply the information filtering techniques to WWW, The application is not so straightforward like Email, Newswire filtering systems. As a result of this study, a simple WWW information filtering system is proposed.

• 디지털산업정보학회논문지
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• 제10권1호
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• pp.61-71
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• 2014

Social networking services have changed the way people communicate. Rapid growth of information generated by social networking services requires effective search methods to give useful results. Over the last decade, social search methods have rapidly evolved. Traditional techniques become unqualified because they ignore social relation data. Existing social recommendation approaches consider social network structure, but social context has not been fully considered. Especially, the friend recommendation is an important feature of SNSs. People tend to trust the opinions of friends they know rather than the opinions of strangers. In this paper, we propose a levelized data processing method for social search in ubiquitous environment. We study previous researches about social search methods in ubiquitous environment. Our method is a new paradigm of levelelized data processing method which can utilize information in social networks, using location and friendship weight. Several experiments are performed and the results verify that the proposed method's performance is better than other existing method.