• Title/Summary/Keyword: SPAN Algorithm

Search Result 191, Processing Time 0.026 seconds

Mining Maximal Frequent Contiguous Sequences in Biological Data Sequences

  • Kang, Tae-Ho;Yoo, Jae-Soo;Kim, Hak-Yong;Lee, Byoung-Yup
    • International Journal of Contents
    • /
    • v.3 no.2
    • /
    • pp.18-24
    • /
    • 2007
  • Biological sequences such as DNA and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of more than hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological datasets with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with a fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. The experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.

Shipyard Skid Sequence Optimization Using a Hybrid Genetic Algorithm

  • Min-Jae Choi;Yung-Keun Kwon
    • Journal of the Korea Society of Computer and Information
    • /
    • v.28 no.12
    • /
    • pp.79-87
    • /
    • 2023
  • In this paper, we propose a novel genetic algorithm to reduce the overall span time by optimizing the skid insertion sequence in the shipyard subassembly process. We represented a solution by a permutation of a set of skid ids and applied genetic operators suitable for such a representation. In addition, we combined the genetic algorithm and the existing heuristic algorithm called UniDev which is properly modified to improve the search performance. In particular, the slow skid search part in UniDev was changed to a greedy algorithm. Through extensive large-scaled simulations, it was observed that the span time of our method was stably minimized compared to Multi-Start search and a genetic algorithm combined with UniDev.

ANALYSIS OF NEIGHBOR-JOINING BASED ON BOX MODEL

  • Cho, Jin-Hwan;Joe, Do-Sang;Kim, Young-Rock
    • Journal of applied mathematics & informatics
    • /
    • v.25 no.1_2
    • /
    • pp.455-470
    • /
    • 2007
  • In phylogenetic tree construction the neighbor-joining algorithm is the most well known method which constructs a trivalent tree from a pairwise distance data measured by DNA sequences. The core part of the algorithm is its cherry picking criterion based on the tree structure of each quartet. We give a generalized version of the criterion based on the exact box model of quartets, known as the tight span of a metric. We also show by experiment why neighbor-joining and the quartet consistency count method give similar performance.

An Incremental Updating Algorithm of Sequential Patterns (점진적인 순차 패턴 갱신 알고리즘)

  • Kim Hak-Ja;Whang Whan-Kyu
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.43 no.5 s.311
    • /
    • pp.17-28
    • /
    • 2006
  • In this paper, we investigate a problem of updating sequential patterns when new transactions are added to a database. We present an efficient updating algorithm for sequential pattern mining that incrementally updates added transactions by reusing frequent patterns found previously. Our performance study shows that this method outperforms both AprioriAll and PrefixSpan algorithm which updates from scratch, since our method can efficiently utilize reduced candidate sets which result from the incremental updating technique.

Reliability analysis of steel cable-stayed bridges including soil-pile interaction

  • Cheng, Jin;Liu, Xiao-luan
    • Steel and Composite Structures
    • /
    • v.13 no.2
    • /
    • pp.109-122
    • /
    • 2012
  • An efficient and accurate algorithm is proposed to evaluate the reliability of cable-stayed bridges accounting for soil-pile interaction. The proposed algorithm integrates the finite-element method and the response surface method. The finite-element method is used to model the cable-stayed bridge including soil-pile interaction. The reliability index is evaluated based on the response surface method. Uncertainties in the superstructure, the substructure and load parameters are incorporated in the proposed algorithm. A long span steel cable-stayed bridge with a main span length of 1088 m built in China is considered as an illustrative example. The reliability of the bridge is evaluated for the strength and serviceability performance functions. Results of the study show that when strength limit states for both girder and tower are considered, soil-pile interaction has significant effects on the reliability of steel cable-stayed bridges. Further, a detailed sensitivity study shows that the modulus of subgrade reaction is the most important soil-pile interaction-related parameter influencing the reliability of steel cable-stayed bridges.

Searching Sequential Patterns by Approximation Algorithm (근사 알고리즘을 이용한 순차패턴 탐색)

  • Sarlsarbold, Garawagchaa;Hwang, Young-Sup
    • Journal of the Korea Society of Computer and Information
    • /
    • v.14 no.5
    • /
    • pp.29-36
    • /
    • 2009
  • Sequential pattern mining, which discovers frequent subsequences as patterns in a sequence database, is an important data mining problem with broad applications. Since a sequential pattern in DNA sequences can be a motif, we studied to find sequential patterns in DNA sequences. Most previously proposed mining algorithms follow the exact matching with a sequential pattern definition. They are not able to work in noisy environments and inaccurate data in practice. Theses problems occurs frequently in DNA sequences which is a biological data. We investigated approximate matching method to deal with those cases. Our idea is based on the observation that all occurrences of a frequent pattern can be classified into groups, which we call approximated pattern. The existing PrefixSpan algorithm can successfully find sequential patterns in a long sequence. We improved the PrefixSpan algorithm to find approximate sequential patterns. The experimental results showed that the number of repeats from the proposed method was 5 times more than that of PrefixSpan when the pattern length is 4.

Mining Maximal Frequent Contiguous Sequences in Biological Data Sequences (생물학적 데이터 서열들에서 빈번한 최대길이 연속 서열 마이닝)

  • Kang, Tae-Ho;Yoo, Jae-Soo
    • The KIPS Transactions:PartD
    • /
    • v.15D no.2
    • /
    • pp.155-162
    • /
    • 2008
  • Biological sequences such as DNA sequences and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological dataset with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with the fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. As the result, the experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.

Reasonably completed state assessment of the self-anchored hybrid cable-stayed suspension bridge: An analytical algorithm

  • Kai Wang;Wen-ming Zhang;Jie Chen;Zhe-hong Zhang
    • Structural Engineering and Mechanics
    • /
    • v.90 no.2
    • /
    • pp.159-175
    • /
    • 2024
  • In order to solve the problem of calculating the reasonable completed bridge state of a self-anchored hybrid cable-stayed suspension bridge (SA-HCSB), this paper proposes an analytical method. This method simplifies the main beam into a continuous beam with multi-point rigid supports and solves the support reaction forces. According to the segmented catenary theory, it simultaneously solves the horizontal forces of the main span main cables and the stay cables and iteratively calculates the equilibrium force system on the main beam in the collaborative system bridge state while completing the shape finding of the main span main cable and stay cables. Then, the horizontal forces of the side span main cables and stay cables are obtained based on the balance of horizontal forces on the bridge towers, and the shape finding of the side spans are completed according to the segmented catenary theory. Next, the difference between the support reaction forces of the continuous beam with multiple rigid supports obtained from the initial and final iterations is used to calculate the load of ballast on the side span main beam. Finally, the axial forces and strains of each segment of the main beam and bridge tower are obtained based on the loads applied by the main cable and stay cables on the main beam and bridge tower, thereby obtaining analytical data for the bridge in the reasonable completed state. In this paper, the rationality and effectiveness of this analytical method are verified through a case study of a SA-HCSB with a main span of 720m in finite element analysis. At the same time, it is also verified that the equilibrium force of the main beam under the reasonably completed bridge state can be obtained through iterative calculation. The analytical algorithm in this paper has clear physical significance, strong applicability, and high accuracy of calculation results, enriching the shape-finding method of this bridge type.

Motion Study for a Humanoid Robot Using Genetic Algorithm (유전 알고리즘을 이용한 휴머노이드 로봇의 동작연구)

  • Kong Jung-Shik;Lee Bo-Hee;Kim Jin-Geol
    • Journal of the Korean Society for Precision Engineering
    • /
    • v.23 no.7 s.184
    • /
    • pp.84-92
    • /
    • 2006
  • This paper deals with determination of motions of a humanoid robot using genetic algorithm. A humanoid robot has some problems of the structural instability basically. So, we have to consider the stable walking gait in gait planning. Besides, it is important to make the smoothly optimal gait for saving the electric power. A mobile robot has battery to move autonomously. But a humanoid robot needs more electric power in order to drive many joints. So, if movements of walking joint don't maintain optimally, it is hard to sustain the battery power during the working period. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. To solve these problems, the genetic algorithm is employed to guarantee the optimal gait trajectory. The fitness functions in a genetic algorithm are introduced to find out optimal trajectory, which enables the robot to have the less reduced jerk of joints and get smooth movement. With these all process accomplished by PC-based program, the optimal solution could be obtained from the simulation. In addition, we discuss the design consideration fur the joint motion and distributed computation of tile humanoid, ISHURO, and suggest its result such as structure of the network and a disturbance observer.

A 3D graphic pipelines with an efficient clipping algorithm (효율적인 클리핑 기능을 갖는 3차원 그래픽 파이프라인 구조)

  • Lee, Chan-Ho
    • Journal of the Institute of Electronics Engineers of Korea SD
    • /
    • v.45 no.8
    • /
    • pp.61-66
    • /
    • 2008
  • Recently, portable devices which require small area and low power consumption employ applications using 3D graphics such as 3D games and 3D graphical user interfaces. We propose an efficient clipping engine algorithm which is suitable in 3D graphics pipeline. The clipping operation is divided into two steps: one is the selection process in the transformation engine and the other is the pixel clipping process in the scan conversion unit. The clipping operation is possible with addition of simple comparator. The clipping for the Y-axis is achieved in the edge walk stage and that for the X and Z-axis is performed in the span processing. The proposed clipping algorithm reduces the operation cycles and the area of of 3D graphics pipelines. We designed a 3D graphics pipeline with the proposed clipping algorithm using Verilog-HDL and verifies the operation using an FPGA.