• 제목/요약/키워드: Search Methods

검색결과 3,836건 처리시간 0.035초

Probability Constrained Search Range Determination for Fast Motion Estimation

  • Kang, Hyun-Soo;Lee, Si-Woong;Hosseini, Hamid Gholam
    • ETRI Journal
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    • 제34권3호
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    • pp.369-378
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    • 2012
  • In this paper, we propose new adaptive search range motion estimation methods where the search ranges are constrained by the probabilities of motion vector differences and a search point sampling technique is applied to the constrained search ranges. Our new methods are based on our previous work, in which the search ranges were analytically determined by the probabilities. Since the proposed adaptive search range motion estimation methods effectively restrict the search ranges instead of search point sampling patterns, they provide a very flexible and hardware-friendly approach in motion estimation. The proposed methods were evaluated and tested with JM16.2 of the H.264/AVC video coding standard. Experiment results exhibit that with negligible degradation in PSNR, the proposed methods considerably reduce the computational complexity in comparison with the conventional methods. In particular, the combined method provides performance similar to that of the hybrid unsymmetrical-cross multi-hexagon-grid search method and outstanding merits in hardware implementation.

Fuzzy Keyword Search Method over Ciphertexts supporting Access Control

  • Mei, Zhuolin;Wu, Bin;Tian, Shengli;Ruan, Yonghui;Cui, Zongmin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권11호
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    • pp.5671-5693
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    • 2017
  • With the rapid development of cloud computing, more and more data owners are motivated to outsource their data to cloud for various benefits. Due to serious privacy concerns, sensitive data should be encrypted before being outsourced to the cloud. However, this results that effective data utilization becomes a very challenging task, such as keyword search over ciphertexts. Although many searchable encryption methods have been proposed, they only support exact keyword search. Thus, misspelled keywords in the query will result in wrong or no matching. Very recently, a few methods extends the search capability to fuzzy keyword search. Some of them may result in inaccurate search results. The other methods need very large indexes which inevitably lead to low search efficiency. Additionally, the above fuzzy keyword search methods do not support access control. In our paper, we propose a searchable encryption method which achieves fuzzy search and access control through algorithm design and Ciphertext-Policy Attribute-based Encryption (CP-ABE). In our method, the index is small and the search results are accurate. We present word pattern which can be used to balance the search efficiency and privacy. Finally, we conduct extensive experiments and analyze the security of the proposed method.

디지털도서관의 통합검색 방식에 관한 연구 (A Study on the Methods of Integrated Search in Digital Libraries Environment)

  • 이수상
    • 한국도서관정보학회지
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    • 제37권2호
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    • pp.127-144
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    • 2006
  • 이 연구는 디지털도서관에서 제공 가능한 통합검색 방식의 유형과 특성을 분석할 목적으로 다음의 세 가지작업을 수행하였다. 첫째, 이용자 관점에서 디지털도서관의 발전단계와 일반적인 통합 방식의 특성을 정리하였다. 둘째, 현재 국내외 대표적인 도서관 포털의 모범사례인 영국의 JISC IE, 미국의 NSDL의 OCKHAM, 그리고 한국의 국가지식포털을 대상으로 통합검색의 현황과 특성에 대하여 검토하였다. 셋째, 디지털도서관에 영역에서 많이 적용되고 있는 통합검색 방식의 유형을 메타통합검색과 분산검색으로 구분하여 각각의 기법적 특성을 도출하였다.

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Likelihood search method with variable division search

  • Koga, Masaru;Hirasawa, Kotaro;Murata, Junichi;Ohbayashi, Masanao
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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    • pp.14-17
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    • 1995
  • Various methods and techniques have been proposed for solving optimization problems; the methods have been applied to various practical problems. However the methods have demerits. The demerits which should be covered are, for example, falling into local minima, or, a slow convergence speed to optimal points. In this paper, Likelihood Search Method (L.S.M.) is proposed for searching for a global optimum systematically and effectively in a single framework, which is not a combination of different methods. The L.S.M. is a sort of a random search method (R.S.M.) and thus can get out of local minima. However exploitation of gradient information makes the L.S.M. superior in convergence speed to the commonly used R.S.M..

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Greedy-based Neighbor Generation Methods of Local Search for the Traveling Salesman Problem

  • Hwang, Junha;Kim, Yongho
    • 한국컴퓨터정보학회논문지
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    • 제27권9호
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    • pp.69-76
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    • 2022
  • 순회 외판원 문제는 가장 유명한 조합 최적화 문제 중 하나이다. 지금까지 이 문제를 해결하기 위해 많은 메타휴리스틱 탐색 알고리즘들이 제안되어 왔으며, 그중의 하나가 지역 탐색이다. 지역 탐색에 있어서 매우 중요한 요소 중 하나가 이웃해 생성 방법으로 주로 역전(inversion)과 같은 무작위 기반 이웃해 생성 방법들이 사용되어 왔다. 본 논문에서는 4가지의 새로운 그리디 기반 이웃해 생성 방법들을 제안한다. 3가지 방법은 그리디 삽입 휴리스틱을 기반으로 하는데, 선택된 도시들을 하나씩 차례로 현재 가장 좋은 위치로 삽입한다. 나머지 하나는 그리디 회전을 기반으로 한다. 제안된 방법들은 대표적인 지역 탐색 알고리즘인 first-choice 언덕 오르기 탐색과 시뮬레이티드 어닐링에 적용된다. 실험을 통해 제안된 그리디 기반 방법들이 기존의 무작위 기반 방법들보다 성능이 우수함을 확인하였다. 또한 일부 그리디 기반 방법들은 기존의 지역 탐색 기법들보다 더 우수함을 확인하였다.

대학생들의 라이프스타일에 의한 외식정보탐색방법이 패스트푸드 전문점 이용 만족에 미치는 영향 (The Influence of Eating-out Information Search Methods on Satisfaction at Fast-food Restaurants According to College Student's Lifestyle)

  • 윤태환
    • 한국식생활문화학회지
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    • 제21권4호
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    • pp.375-380
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    • 2006
  • The purpose of this study was to research eating-out information search methods according to college student's lifestyle and their influences on overall satisfaction at fast-food restaurants in eastern province of Kangwondo. Lifestyle was divided into 7 factors and 6 clusters. According to the results, information search methods through Newspaper, magazine and word of mouth were used the most preferably by Cluster 3, 'Brand preference intention'. And TV advertising was used the most preferably by Cluster 4, 'Convenience intention', and the advertisement through internet was used the most preferably by Cluster 5, 'Health ${\cdot}$ effort intention'. However, Information searches through TV advertising and word of mouth had negative influence on the overall satisfaction. But method through internet had positive influences on the overall satisfaction. Eventually, it's proved that information search methods had significant differences according to student's lifestyle. And some information search methods influenced their overall satisfaction. Therefore, food-sonics corporations need to try reducing negative images of various advertisements and activating positive aspects of specialized promotion instruments.

A SELF SCALING MULTI-STEP RANK ONE PATTERN SEARCH ALGORITHM

  • Moghrabi, Issam A.R.
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제15권4호
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    • pp.267-275
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    • 2011
  • This paper proposes a new quickly convergent pattern search quasi-Newton algorithm that employs the multi-step version of the Symmetric Rank One (SRI). The new algorithm works on the factorizations of the inverse Hessian approximations to make available a sequence of convergent positive bases required by the pattern search process. The algorithm, in principle, resembles that developed in [1] with multi-step methods dominating the dervation and with numerical improvements incurred, as shown by the numerical results presented herein.

Subset selection in multiple linear regression: An improved Tabu search

  • Bae, Jaegug;Kim, Jung-Tae;Kim, Jae-Hwan
    • Journal of Advanced Marine Engineering and Technology
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    • 제40권2호
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    • pp.138-145
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    • 2016
  • This paper proposes an improved tabu search method for subset selection in multiple linear regression models. Variable selection is a vital combinatorial optimization problem in multivariate statistics. The selection of the optimal subset of variables is necessary in order to reliably construct a multiple linear regression model. Its applications widely range from machine learning, timeseries prediction, and multi-class classification to noise detection. Since this problem has NP-complete nature, it becomes more difficult to find the optimal solution as the number of variables increases. Two typical metaheuristic methods have been developed to tackle the problem: the tabu search algorithm and hybrid genetic and simulated annealing algorithm. However, these two methods have shortcomings. The tabu search method requires a large amount of computing time, and the hybrid algorithm produces a less accurate solution. To overcome the shortcomings of these methods, we propose an improved tabu search algorithm to reduce moves of the neighborhood and to adopt an effective move search strategy. To evaluate the performance of the proposed method, comparative studies are performed on small literature data sets and on large simulation data sets. Computational results show that the proposed method outperforms two metaheuristic methods in terms of the computing time and solution quality.

FUNDAMENTAL PERFORMANCE OF IMAGE CODING SCHEMES BASED ON MULTIPULSE MODEL

  • Kashiwagi, Takashi;Kobayashi, Daisuke;Koda, Hiromu
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.825-829
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    • 2009
  • In this paper, we examine the fundamental performance of image coding schemes based on multipulse model. First, we introduce several kinds of pulse search methods (i.e., correlation method, pulse overlap search method and pulse amplitude optimization method) for the model. These pulse search methods are derived from auto-correlation function of impulse responses and cross-correlation function between host signals and impulse responses. Next, we explain the basic procedure of multipulse image coding scheme, which uses the above pulse search methods in order to encode the high frequency component of an original image. Finally, by means of computer simulation for some test images, we examine the PSNR(Peak Signal-to-Noise Ratio) and computational complexity of these methods.

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저전력 움직임 추정을 위한 데이터 재사용 스캔 방법 (Data Reusable Search Scan Methods for Low Power motion Estimation)

  • 김태선;선우명훈
    • 전자공학회논문지
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    • 제50권9호
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    • pp.85-91
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    • 2013
  • 본 논문은 저전력 움직임 추정장치를 구현하기 위한 전역 탐색 및 고속 탐색용 데이터 재사용 스캔 방법을 제안한다. 제안하는 최적화된 소 구역 분할방법은 탐색 영역을 여러 개의 소 구역으로 나누어 기존의 smart snake scan 방법과 비교 하였을때 같은 양의 데이터 재사용에 필요한 재구성 가능한 레지스터 어레이를 반으로 줄일 수 있다. 또한 제안하는 중심 편향 탐색 스캔방법은 다양한 고속탐색 알고리즘의 데이터 재사용 가능성을 향상 시킬 수 있다. 제안하는 탐색 순서는 기존의 래스터 스캔과 snake scan 방법에 비해 평균적으로 각각 26%와 16.1%의 반복된 데이터 로딩을 줄일 수 있다. 따라서 제안하는 스캔 방법은 메모리의 접근 횟수를 줄일 수 있기 때문에 저전력과 고성능의 움직임 추정 구현에 적합하다.