• Title/Summary/Keyword: Sequential Tree

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Tree-based Navigation Pattern Analysis

  • Choi, Hyun-Jip
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.271-279
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    • 2001
  • Sequential pattern discovery is one of main interests in web usage mining. the technique of sequential pattern discovery attempts to find inter-session patterns such that the presence of a set of items is followed by another item in a time-ordered set of server sessions. In this paper, a tree-based sequential pattern finding method is proposed in order to discover navigation patterns in server sessions. At each learning process, the suggested method learns about the navigation patterns per server session and summarized into the modified Rymon's tree.

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Note on classification and regression tree analysis (분류와 회귀나무분석에 관한 소고)

  • 임용빈;오만숙
    • Journal of Korean Society for Quality Management
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    • v.30 no.1
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    • pp.152-161
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    • 2002
  • The analysis of large data sets with hundreds of thousands observations and thousands of independent variables is a formidable computational task. A less parametric method, capable of identifying important independent variables and their interactions, is a tree structured approach to regression and classification. It gives a graphical and often illuminating way of looking at data in classification and regression problems. In this paper, we have reviewed and summarized tile methodology used to construct a tree, multiple trees and the sequential strategy for identifying active compounds in large chemical databases.

Efficiently Managing the B-tree using Write Pattern Conversion on NAND Flash Memory (낸드 플래시 메모리 상에서 쓰기 패턴 변환을 통한 효율적인 B-트리 관리)

  • Park, Bong-Joo;Choi, Hae-Gi
    • Journal of KIISE:Computer Systems and Theory
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    • v.36 no.6
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    • pp.521-531
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    • 2009
  • Flash memory has physical characteristics different from hard disk where two costs of a read and write operations differ each other and an overwrite on flash memory is impossible to be done. In order to solve these restrictions with software, storage systems equipped with flash memory deploy FTL(Flash Translation Layer) software. Several FTL algorithms have been suggested so far and most of them prefer sequential write pattern to random write pattern. In this paper, we provide a new technique to efficiently store and maintain the B-tree index on flash memory. The operations like inserts, deletes, updates of keys for the B-tree generate random writes rather than sequential writes on flash memory, leading to inefficiency to the B-tree maintenance. In our technique, we convert random writes generated by the B-tree into sequential writes and then store them to the write-buffer on flash memory. If the buffer is full later, some sequential writes in the buffer will be issued to FTL. Our diverse experimental results show that our technique outperforms the existing ones with respect to the I/O cost of flash memory.

Sequential and Parallel Algorithms for Finding a Longest Non-negative Path in a Tree (트리에서 가장 긴 비음수 경로를 찾는 직렬 및 병렬 알고리즘)

  • Kim, Sung-Kwon
    • Journal of KIISE:Computer Systems and Theory
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    • v.33 no.12
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    • pp.880-884
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    • 2006
  • In an edge-weighted(positive, negative, or zero weights are possible) tree, we want to solve the problem of finding a longest path such that the sum of the weights of the edges in tile path is non-negative. To find a longest non-negative path of a tree we present a sequential algorithm with O(n logn) time and a CREW PRAM parallel algorithm with $O(log^2n)$ time and O(n) processors. where n is the number of nodes in the tree.

Sequential prediction of TBM penetration rate using a gradient boosted regression tree during tunneling

  • Lee, Hang-Lo;Song, Ki-Il;Qi, Chongchong;Kim, Kyoung-Yul
    • Geomechanics and Engineering
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    • v.29 no.5
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    • pp.523-533
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    • 2022
  • Several prediction model of penetration rate (PR) of tunnel boring machines (TBMs) have been focused on applying to design stage. In construction stage, however, the expected PR and its trends are changed during tunneling owing to TBM excavation skills and the gap between the investigated and actual geological conditions. Monitoring the PR during tunneling is crucial to rescheduling the excavation plan in real-time. This study proposes a sequential prediction method applicable in the construction stage. Geological and TBM operating data are collected from Gunpo cable tunnel in Korea, and preprocessed through normalization and augmentation. The results show that the sequential prediction for 1 ring unit prediction distance (UPD) is R2≥0.79; whereas, a one-step prediction is R2≤0.30. In modeling algorithm, a gradient boosted regression tree (GBRT) outperformed a least square-based linear regression in sequential prediction method. For practical use, a simple equation between the R2 and UPD is proposed. When UPD increases R2 decreases exponentially; In particular, UPD at R2=0.60 is calculated as 28 rings using the equation. Such a time interval will provide enough time for decision-making. Evidently, the UPD can be adjusted depending on other project and the R2 value targeted by an operator. Therefore, a calculation process for the equation between the R2 and UPD is addressed.

Parallel and Sequential Implementation to Minimize the Time for Data Transmission Using Steiner Trees

  • Anand, V.;Sairam, N.
    • Journal of Information Processing Systems
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    • v.13 no.1
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    • pp.104-113
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    • 2017
  • In this paper, we present an approach to transmit data from the source to the destination through a minimal path (least-cost path) in a computer network of n nodes. The motivation behind our approach is to address the problem of finding a minimal path between the source and destination. From the work we have studied, we found that a Steiner tree with bounded Steiner vertices offers a good solution. A novel algorithm to construct a Steiner tree with vertices and bounded Steiner vertices is proposed in this paper. The algorithm finds a path from each source to each destination at a minimum cost and minimum number of Steiner vertices. We propose both the sequential and parallel versions. We also conducted a comparative study of sequential and parallel versions based on time complexity, which proved that parallel implementation is more efficient than sequential.

Wine Quality Assessment Using a Decision Tree with the Features Recommended by the Sequential Forward Selection

  • Lee, Seunghan;Kang, Kyungtae;Noh, Dong Kun
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.2
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    • pp.81-87
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    • 2017
  • Nowadays wine is increasingly enjoyed by a wider range of consumers, and wine certification and quality assessment are key elements in supporting the wine industry to develop new technologies for both wine making and selling processes. There have been many attempts to construct a more methodical approach to the assessment of wines, but most of them rely on objective decision rather than subjective judgement. In this paper, we propose a data mining approach to predict human wine taste preferences that is based on easily available analytical tests at the certification step. We used sequential forward selection and decision tree for this purpose. Experiments with the wine quality dataset from the UC Irvine Machine Learning Repository demonstrate the accuracies of 76.7% and 78.7% for red and white wines respectively.

Construction of UOWHF: New Parallel Domain Extender with Optimal Key Size (UOWHF 구생방법 : 최적의 키 길이를 가자는 새로운 병렬 도메인 확장기)

  • Wonil Lee;Donghoon Chang
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.14 no.2
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    • pp.57-68
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    • 2004
  • We present a new parallel algorithm for extending the domain of a UOWHF. Our algorithm is based on non-complete l-ary tree and has the same optimal key length expansion as Shoup's which has the most efficient key length expansion known so far. Using the recent result [8], we can also prove that the key length expansion of this algorithm and Shoup's sequential algorithm are the minimum possible for any algorithms in a large class of "natural" domain extending algorithms. But its prallelizability performance is less efficient than complete tree based constructions. However if l is getting larger then the parallelizability of the construction is also getting near to that of complete tree based constructions.tructions.

Comparison of Classification Models for Sequential Flight Test Results (단계별 비행훈련 성패 예측 모형의 성능 비교 연구)

  • Sohn, So-Young;Cho, Yong-Kwan;Choi, Sung-Ok;Kim, Young-Joun
    • Journal of the Ergonomics Society of Korea
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    • v.21 no.1
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    • pp.1-14
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    • 2002
  • The main purpose of this paper is to present selection criteria for ROK Airforce pilot training candidates in order to save costs involved in sequential pilot training. We use classification models such Decision Tree, Logistic Regression and Neural Network based on aptitude test results of 288 ROK Air Force applicants in 1994-1996. Different models are compared in terms of classification accuracy, ROC and Lift-value. Neural network is evaluated as the best model for each sequential flight test result while Logistic regression model outperforms the rest of them for discriminating the last flight test result. Therefore we suggest a pilot selection criterion based on this logistic regression. Overall. we find that the factors such as Attention Sharing, Speed Tracking, Machine Comprehension and Instrument Reading Ability having significant effects on the flight results. We expect that the use of our criteria can increase the effectiveness of flight resources.

Diagnostics of Treeing Degradation in Organic Insulating Materials by Image Processing

  • Noboru-Yoshimura
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 1990.10a
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    • pp.1-16
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    • 1990
  • In this paper, a system to measure treeing degradation phenomena in organic insulating materials, using an image sensor, is discussed. Using an image processing technique, tree features immediately after tree initiation as well as changes in the configuration of the tree were measured. which up to now have been extremely difficult to observe by conventional visual methods. As a result, it was possible to record the image of tree propagation immediately after its first appearance, and to describe the specific characteristics of tree growth in terms of the length, the degraded area and the sequential images.