• 제목/요약/키워드: Sort-Sorting

검색결과 79건 처리시간 0.022초

전 분류 기법과 후 분류 기법의 조합을 통한 효율적 병렬 타일 가시화 알고리듬 개발 (Development of Efficient Parallel Tiled Display Algorithms by Combining the Sort-first and the Sort-last Sorting Methods)

  • 최윤혁;김일호;김홍성;조진연
    • 한국항공우주학회지
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    • 제36권2호
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    • pp.146-155
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    • 2008
  • 본 논문에서는 고해상도 타일 가시화 시스템의 성능 향상을 위해 전 분류 기법과 후 분류 기법을 조합하여 두 가지 병렬-타일 가시화 알고리듬을 제안하였다. 전 분류에서는 디스플레이 리스트와 시각 절두체 선별 기법을 이용하였으며, 후 분류에서는 선 탐색 부분 후 분류기법을 이용하였다. 벤치마킹 테스트를 통해 제안된 두 병렬-타일 가시화 기법의 성능을 고찰하였으며, 이 결과를 기반으로 제안된 두 가지 병렬-타일 가시화 알고리듬 중에서 주어진 가시화 모델에 대해 더 효율적인 알고리듬을 선정하는 방안을 제시하였다.

Analysis and Comparison of Sorting Algorithms (Insertion, Merge, and Heap) Using Java

  • Khaznah, Alhajri;Wala, Alsinan;Sahar, Almuhaishi;Fatimah, Alhmood;Narjis, AlJumaia;Azza., A.A
    • International Journal of Computer Science & Network Security
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    • 제22권12호
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    • pp.197-204
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    • 2022
  • Sorting is an important data structure in many applications in the real world. Several sorting algorithms are currently in use for searching and other operations. Sorting algorithms rearrange the elements of an array or list based on the elements' comparison operators. The comparison operator is used in the accurate data structure to establish the new order of elements. This report analyzes and compares the time complexity and running time theoretically and experimentally of insertion, merge, and heap sort algorithms. Java language is used by the NetBeans tool to implement the code of the algorithms. The results show that when dealing with sorted elements, insertion sort has a faster running time than merge and heap algorithms. When it comes to dealing with a large number of elements, it is better to use the merge sort. For the number of comparisons for each algorithm, the insertion sort has the highest number of comparisons.

DESIGN AND ANALYSIS OF PREDICTIVE SORTING ALGORITHMS

  • Yun, Min-Young
    • Journal of applied mathematics & informatics
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    • 제3권1호
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    • pp.11-24
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    • 1996
  • The focus of this research is the class of sequential al-gorithms called predictive sorting algorithms for sorting a given set of n elements using pairwise comparisons. The order in which these pairwise comparisons are made is defined by a fixed sequence of all un-ordered pairs of distinct integers{1,2 ···,n} called a sort sequence. A predictive sorting algorithm associated with a sort sequence spec-ifies pairwise comparisons of elements in the input set in the order defined by the sort sequence except that the comparisons whose out-comes can be inferred from the preceding pairs of comparisons are not performed. in this paper predictive sorting algorithms are obtained based on known sorting algorithms and are shown to be required on the average O(n log n) comparisons.

THE CHARACTERIZATION OF SORT SEQUENCES

  • Yun, MIn-Young
    • Journal of applied mathematics & informatics
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    • 제4권2호
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    • pp.513-528
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    • 1997
  • A sort sequence $S_n$ is a sequence of all unordered pairs of indices in $I_n\;=\;{1,\;2,v...,\;n}$. With a sort sequence Sn we assicuate a sorting algorithm ($AS_n$) to sort input set $X\;=\;{x_1,\;x_2,\;...,\;x_n}$ as follows. An execution of the algorithm performs pairwise comparisons of elements in the input set X as defined by the sort sequence $S_n$, except that the comparisons whose outcomes can be inferred from the outcomes of the previous comparisons are not performed. Let $X(S_n)$ denote the acverage number of comparisons required by the algorithm $AS_n$ assuming all input orderings are equally likely. Let $X^{\ast}(n)\;and\;X^{\circ}(n)$ denote the minimum and maximum value respectively of $X(S_n)$ over all sort sequences $S_n$. Exact determination of $X^{\ast}(n),\;X^{\circ}(n)$ and associated extremal sort sequenes seems difficult. Here, we obtain bounds on $X^{\ast}(n)\;and\;X^{\circ}(n)$.

ON EXTREMAL SORT SEQUENCES

  • Yun, Min-Young;Keum, Young-Wook
    • Journal of applied mathematics & informatics
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    • 제9권1호
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    • pp.239-252
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    • 2002
  • A sort sequence $S_n$ is sequence of all unordered pairs of indices in $I_n$={1,2,…n}. With a sort sequence $S_n$ = ($s_1,S_2,...,S_{\frac{n}{2}}$),one can associate a predictive sorting algorithm A($S_n$). An execution of the a1gorithm performs pairwise comparisons of elements in the input set X in the order defined by the sort sequence $S_n$ except that the comparisons whose outcomes can be inferred from the results of the preceding comparisons are not performed. A sort sequence is said to be extremal if it maximizes a given objective function. First we consider the extremal sort sequences with respect to the objective function $\omega$($S_n$) - the expected number of tractive predictions in $S_n$. We study $\omega$-extremal sort sequences in terms of their prediction vectors. Then we consider the objective function $\Omega$($S_n$) - the minimum number of active predictions in $S_n$ over all input orderings.

CSP의 Multi-sorting을 위한 pick and place 시스템의 개발 (The development of Pick and place system for multi-sorting of CSP)

  • 김찬용;곽철훈;이은상
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1997년도 추계학술대회 논문집
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    • pp.171-174
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    • 1997
  • The great development of semiconductor industry demands the high efficiency and performance of related device, but the pick and place system of semiconductor packaging device can load a few units until nowdays. Although the system can load a lot of units, it can work multiple sort operation. The defect like that causes a low efficiency. Therefore, this paper represents the development of pick and place system which can work multiple sort operation.

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Development of YOLO-based apple quality sorter

  • Donggun Lee;Jooseon Oh;Youngtae Choi;Donggeon Lee;Hongjeong Lee;Sung-Bo Shim;Yushin Ha
    • 농업과학연구
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    • 제50권3호
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    • pp.415-424
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    • 2023
  • The task of sorting and excluding blemished apples and others that lack commercial appeal is currently performed manually by human eye sorting, which not only causes musculoskeletal disorders in workers but also requires a significant amount of time and labor. In this study, an automated apple-sorting machine was developed to prevent musculoskeletal disorders in apple production workers and to streamline the process of sorting blemished and non-marketable apples from the better quality fruit. The apple-sorting machine is composed of an arm-rest, a main body, and a height-adjustable part, and uses object detection through a machine learning technology called 'You Only Look Once (YOLO)' to sort the apples. The machine was initially trained using apple image data, RoboFlow, and Google Colab, and the resulting images were analyzed using Jetson Nano. An algorithm was developed to link the Jetson Nano outputs and the conveyor belt to classify the analyzed apple images. This apple-sorting machine can immediately sort and exclude apples with surface defects, thereby reducing the time needed to sort the fruit and, accordingly, achieving cuts in labor costs. Furthermore, the apple-sorting machine can produce uniform quality sorting with a high level of accuracy compared with the subjective judgment of manual sorting by eye. This is expected to improve the productivity of apple growing operations and increase profitability.

유전 알고리즘을 이용한 정렬 알고리즘의 최악의 인스턴스 탐색 (Finding the Worst-case Instances of Some Sorting Algorithms Using Genetic Algorithms)

  • 전소영;김용혁
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2010년도 한국컴퓨터종합학술대회논문집 Vol.37 No.1(B)
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    • pp.1-5
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    • 2010
  • 정렬 알고리즘에서 사용한 원소 간 비교횟수를 기준으로, 비교횟수가 많게 되는 순열을 최악의 인스턴스(worst-case instance)라 명명하고 이를 찾기 위해 유전 알고리즘(genetic algorithm)을 사용하였다. 잘 알려진 퀵 정렬(quick sort), 머지 정렬(merge sort), 힙 정렬(heap sort), 삽입 정렬(insertion sort), 쉘 정렬(shell sort), 개선된 퀵 정렬(advanced quick sort)에 대해서 실험하였다. 머지 정렬과 삽입 정렬에 대해 탐색한 인스턴스는 최악의 인스턴스에 거의 근접하였다. 퀵 정렬은 크기가 증가함에 따라 최악의 인스턴스 탐색이 어려웠다. 나머지 정렬에 대해서 찾은 인스턴스는 최악의 인스턴스인지 이론적으로 보장할 수 없지만, 임의의 1,000개 순열을 정렬해서 얻은 비교횟수들의 평균치보다는 훨씬 높았다. 본 논문의 최악의 인스턴스를 탐색하는 시도는 알고리즘의 성능 검증을 위한 테스트 데이터를 생성한다는 점에서 의미가 크다.

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A Fast Sorting Strategy Based on a Two-way Merge Sort for Balancing the Capacitor Voltages in Modular Multilevel Converters

  • Zhao, Fangzhou;Xiao, Guochun;Liu, Min;Yang, Daoshu
    • Journal of Power Electronics
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    • 제17권2호
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    • pp.346-357
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    • 2017
  • The Modular Multilevel Converter (MMC) is particularly attractive for medium and high power applications such as High-Voltage Direct Current (HVDC) systems. In order to reach a high voltage, the number of cascaded submodules (SMs) is generally very large. Thus, in the applications with hundreds or even thousands of SMs such as MMC-HVDCs, the sorting algorithm of the conventional voltage balancing strategy is extremely slow. This complicates the controller design and increases the hardware cost tremendously. This paper presents a Two-Way Merge Sort (TWMS) strategy based on the prediction of the capacitor voltages under ideal conditions. It also proposes an innovative Insertion Sort Correction for the TWMS (ISC-TWMS) to solve issues in practical engineering under non-ideal conditions. The proposed sorting methods are combined with the features of the MMC-HVDC control strategy, which significantly accelerates the sorting process and reduces the implementation efforts. In comparison with the commonly used quicksort algorithm, it saves at least two-thirds of the sorting execution time in one arm with 100 SMs, and saves more with a higher number of SMs. A 501-level MMC-HVDC simulation model in PSCAD/EMTDC has been built to verify the validity of the proposed strategies. The fast speed and high efficiency of the algorithms are demonstrated by experiments with a DSP controller (TMS320F28335).

저속 네트웍 PC 클러스터상에서 NOW-Sort의 성능향상 (Enhanced NOW-Sort on a PC Cluster with a Low-Speed Network)

  • 김지형;김동승
    • 한국정보과학회논문지:시스템및이론
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    • 제29권10호
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    • pp.550-560
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    • 2002
  • 병렬 외부정렬을 클러스터형 분산 컴퓨터에서 실행하는 경우에는 순수하게 주메모리에서 부분적인 정렬과 머지를 위해 실행되는 과정(순수 계산)뿐만 아니라 디스크로부터의 입출력 과정 및 각 노드들간의 데이타 교환에 따르는 통신과정을 적절히 배치, 설계함이 필요하다. 그 주된 이유는 전체 수행시간이 순수 계산시판보다는 디스크 입출력에 소요되는 시간 및 통신의 소요시간의 비중이 크기 때문이다. 본 연구에서는 저속 네트웍 PC 클러스터를 계산도구로 하여 단위시간당 정렬 자료규모를 최대화함을 목표로 하여, 알고리즘적인 최적화를 통해서, 즉, 정렬 도중 통신과정에서 발생하는 지체시간을 최소화하여 전체적인 통신 성능을 높이고, 디스크 입출력 작업은 전송 규모와 횟수를 조절하여 계산과 통신작업등과의 중첩정도를 극대화시켜 외부정렬의 성능을 개선하였다. 실험 결과 새 알고리즘이 기존의 NOW-sort 알고리즘[1]에 비해서 동일한 PC 클러스터 경에서 최대 45% 정도까지 실행시간을 단축시킬 수 있고, 확장성 면에 있어서도 더 우수한 것을 확인하였다.