• Title/Summary/Keyword: Sorting algorithm

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Effect of Learning a Divide-and-conquer Algorithm on Creative Problem Solving (분할 정복 알고리즘 학습이 창의적 문제 해결에 미치는 효과)

  • Kim, Yoon Young;Kim, Yungsik
    • The Journal of Korean Association of Computer Education
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    • v.16 no.2
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    • pp.9-18
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    • 2013
  • In secondary education, learning a computer science subject has the purpose to improve creative problem solving ability of students by learning computational thinking and principles. In particular, learning algorithm has been emphasized for this purpose. There are studies that learning algorithm has the effect of creative problem solving based on the leading studies that learning algorithm has the effect of problem solving. However, relatively the importance of the learning algorithm can weaken, because these studies depend on creative problem solving model or special contents for creativity. So this study proves that learning algorithm has the effect of creative problem solving in the view that common problem solving and creative problem solving have the same process. For this, analogical reasoning was selected among common thinking skills and divide-and-conquer algorithm was selected among abstractive principles for analogical reasoning in sorting algorithm. The frequency which solves the search problem by using the binary search algorithm was higher than the control group learning only sequence of sorting algorithm about the experimental group learning divide-and-conquer algorithm. This result means that learning algorithm including abstractive principle like divide-and-conquer has the effect of creative problem solving by analogical reasoning.

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Multi-Objective Genetic Algorithm for Machine Selection in Dynamic Process Planning (동적 공정계획에서의 기계선정을 위한 다목적 유전자 알고리즘)

  • Choi, Hoe-Ryeon;Kim, Jae-Kwan;Lee, Hong-Chul;Rho, Hyung-Min
    • Journal of the Korean Society for Precision Engineering
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    • v.24 no.4 s.193
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    • pp.84-92
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    • 2007
  • Dynamic process planning requires not only more flexible capabilities of a CAPP system but also higher utility of the generated process plans. In order to meet the requirements, this paper develops an algorithm that can select machines for the machining operations by calculating the machine loads. The developed algorithm is based on the multi-objective genetic algorithm that gives rise to a set of optimal solutions (in general, known as the Pareto-optimal solutions). The objective is to satisfy both the minimization number of part movements and the maximization of machine utilization. The algorithm is characterized by a new and efficient method for nondominated sorting through K-means algorithm, which can speed up the running time, as well as a method of two stages for genetic operations, which can maintain a diverse set of solutions. The performance of the algorithm is evaluated by comparing with another multiple objective genetic algorithm, called NSGA-II and branch and bound algorithm.

Development of On-line Grading Algorithm of Green Pepper Using Machine Vision (기계시각에 의한 풋고추 온라인 등급판정 알고리즘 개발)

  • Cho, N. H.;Lee, S. H.;Hwang, H.;Lee, Y. H.;Choi, S. M.;Park, J. R.;Cho, K. H.
    • Journal of Biosystems Engineering
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    • v.26 no.6
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    • pp.571-578
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    • 2001
  • Production of green pepper has increased for ten years in Korea, as customer's preference of a pepper tuned to fiesta one. This study was conducted to develop an on-line fading algorithm of green pepper using machine vision and aimed to develop the automatic on-line grading and sorting system. The machine vision system was composed of a professive scan R7B CCD camera, a frame grabber and sets of 3-wave fluorescent lamps. The length and curvature, which were main quality factors of a green pepper were measured while removing the stem region. The first derivative of the thickness profile was used to remove the stem area of the segmented image of the pepper. A new boundary was generated after the stem was removed and a baseline of a pepper which was used for the curvature determination was also generated. The developed algorithm showed that the accuracy of the size measurement was 86.6% and the accuracy of the bent was 91.9%. Processing time spent far grading was around 0.17 sec per pepper.

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Multi-Objective Genetic Algorithm based on Multi-Robot Positions for Scheduling Problems (스케줄링 문제를 위한 멀티로봇 위치 기반 다목적 유전 알고리즘)

  • Choi, Jong Hoon;Kim, Je Seok;Jeong, Jin Han;Kim, Jung Min;Park, Jahng Hyon
    • Journal of the Korean Society for Precision Engineering
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    • v.31 no.8
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    • pp.689-696
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    • 2014
  • This paper presents a scheduling problem for a high-density robotic workcell using multi-objective genetic algorithm. We propose a new algorithm based on NSGA-II(Non-dominated Sorting Algorithm-II) which is the most popular algorithm to solve multi-objective optimization problems. To solve the problem efficiently, the proposed algorithm divides the problem into two processes: clustering and scheduling. In clustering process, we focus on multi-robot positions because they are fixed in manufacturing system and have a great effect on task distribution. We test the algorithm by changing multi-robot positions and compare it to previous work. Test results shows that the proposed algorithm is effective under various conditions.

A Parallel Finite Element Procedure for Contact-Impact Problems (충돌해석을 위한 병렬유한요소 알고리즘)

  • Har, Jason
    • Proceedings of the KSME Conference
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    • 2003.11a
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    • pp.1286-1290
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    • 2003
  • This paper presents a newly implemented parallel finite element procedure for contact-impact problems. Three sub-algorithms are includes in the proposed parallel contact-impact procedure, such as a parallel Belytschko-Lin-Tsay (BLT) shell element generation, a parallel explicit time integration scheme, and a parallel contact search algorithm based on the master slave slide-line algorithm. The underlying focus of the algorithms is on its effectiveness and efficiency for inclusion in future finite element systems on parallel computers. Throughout this research, a prototype code, named GT-PARADYN, is developed on the IBM SP2, a distributed-memory computer. Some numerical examples are provided to demonstrate the timing results of the procedure, discussing the accuracy and efficiency of the code.

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Computer Vision System for Automatic Grading of Ginseng - Development of Image Processing Algorithms - (인삼선별의 자동화를 위한 컴퓨터 시각장치 - 등급 자동판정을 위한 영상처리 알고리즘 개발 -)

  • 김철수;이중용
    • Journal of Biosystems Engineering
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    • v.22 no.2
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    • pp.227-236
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    • 1997
  • Manual grading and sorting of red-ginsengs are inherently unreliable due to its subjective nature. A computerized technique based on optical and geometrical characteristics was studied for the objective quality evalution. Spectral reflectance of three categories of red-ginsengs - "Chunsam", "Chisam", "Yangsam" - were measured and analyzed. Variation of reflectance among parts of a single ginseng was more significant than variation among the quality categories of ginsengs. A PC-based image processing algorithm was developed to extract geometrical features such as length and thickness of body, length and number of roots, position of head and branch point, etc. The algorithm consisted of image segmentation, calculation of Euclidean distance, skeletonization and feature extraction. Performance of the algorithm was evaluated using sample ginseng images and found to be mostly sussessful.

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An Optimal Parallel Sort Algorithm for Minimum Data Movement (최소 자료 이동을 위한 최적 병렬 정렬 알고리즘)

  • Hong, Seong-Su;Sim, Jae-Hong
    • The Transactions of the Korea Information Processing Society
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    • v.1 no.3
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    • pp.290-298
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    • 1994
  • In this paper we propose parallel sorting algorithm, taking 0( $n^{n}$ log n) time complexity, 0( $n^{x}$ log n) cost (parallel running time * number of processors) and 0( $n^{1-}$x+ $n^{x}$ )data movement complexity under the ERWW- PRAM model. The methods for solving these problems similar. Parallel algorithm finds pivot for partitioning the data into ordered subsets of approximately equal size by using encording pointers..

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Machine load prediction for selecting machines in machining (절삭가공에서의 기계선정을 위한 기계부하 예측)

  • Choi H.R.;Kim J.K.;Rho H.M.;Lee H.C.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.997-1000
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    • 2005
  • Dynamic job shop environment requires not only more flexible capabilities of a CAPP system but higher utility of the generated process plans. In order to meet the requirements, this paper develops an algorithm that can select machines for the machining operations to be performed by predicting the machine loads. The developed algorithm is based on the multiple objective genetic algorithm that gives rise to a set of optimal solutions (in general, known as Pareto-optimal solutions). The objective shows a combination of the minimization of part movement and the maximization of machine utility balance. The algorithm is characterized by a new and efficient method for nondominated sorting, which can speed up the running time, as well as a method of two stages for genetic operations, which can maintain a diverse set of solutions. The performance of the algorithm is evaluated by comparing with another multiple objective genetic algorithm, called NSGA-II.

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An Adaptive and Fast Motion Estimation Algorithm using Initial Matching Errors (초기 매칭 에러를 통한 적응적 고속 움직임 예측 알고리즘)

  • Jeong, Tae-Il
    • Journal of Korea Multimedia Society
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    • v.10 no.11
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    • pp.1439-1445
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    • 2007
  • In this paper, we propose a fast motion estimation algorithm using initial matching errors by sorting square sub-blocks to find complex sub-block area adaptively based on partial calculation of SAD(sum of absolute difference) while keeping the same prediction quality compared with the PDE(partial distortion elimination) algorithm. We reduced unnecessary calculations with square sub-block adaptive matching scan based initial SAD calculation of square sub-block in each matching block. Our algorithm reduces about 45% of computations for block matching error compared with conventional PDE(partial distortion elimination) algorithm without any degradation of prediction quality, and for algorithm will be useful to real-time video coding applications using MPEG-4 AVC or MPEG-2.

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A New Multi-objective Evolutionary Algorithm for Inter-Cloud Service Composition

  • Liu, Li;Gu, Shuxian;Fu, Dongmei;Zhang, Miao;Buyya, Rajkumar
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.1
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    • pp.1-20
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    • 2018
  • Service composition in the Inter-Cloud raises new challenges that are caused by the different Quality of Service (QoS) requirements of the users, which are served by different geo-distributed Cloud providers. This paper aims to explore how to select and compose such services while considering how to reach high efficiency on cost and response time, low network latency, and high reliability across multiple Cloud providers. A new hybrid multi-objective evolutionary algorithm to perform the above task called LS-NSGA-II-DE is proposed, in which the differential evolution (DE) algorithm uses the adaptive mutation operator and crossover operator to replace the those of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to get the better convergence and diversity. At the same time, a Local Search (LS) method is performed for the Non-dominated solution set F{1} in each generation to improve the distribution of the F{1}. The simulation results show that our proposed algorithm performs well in terms of the solution distribution and convergence, and in addition, the optimality ability and scalability are better compared with those of the other algorithms.