Search Results - (( java segmentation using algorithm ) OR ( using control chart algorithm ))

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  1. 1

    ROAD algorithm for control charts / Gejza Dohnal by Dohnal, Gejza

    Published 2015
    “…Using with robust control chart we obtain a robust adaptive control chart (ROAD). …”
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    Conference or Workshop Item
  2. 2

    Construction of fuzzy control charts by using triangular and gaussian fuzzy numbers for solder paste thickness by Ahmad Basri, Nur Ain Zafirah

    Published 2018
    “…This study aims to generate fuzzy numbers by using triangular and Gaussian approaches and to analyse the algorithm of fuzzy control charts by using α-cut and to analyse the algorithm of traditional control charts of -R and -S towards the solder paste thickness of integrated circuit data. …”
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    Thesis
  3. 3

    Fiducial registration error as a statistical process control metric in image-guidance radiotherapy with fiducial markers by Ung, N.M., Wee, L.

    Published 2011
    “…A procedure for estimating control parameters of a SPC control chart (x-chart) from a small number of initial observations (N) of FRE was implemented. …”
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    Article
  4. 4

    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC) by Ibrahim, Kamarul 'Asri, Ahmad, Arshad, Ali, Mohamad Wijayanuddin, Mak, Weng Yee

    Published 2006
    “…Shewhart Control Chart (SCC) and Range Control Chart (RCC) are used with the developed correlation coefficients for FDD. …”
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    Monograph
  5. 5

    Development Of Two New Auxiliary Information Control Charts, And Economic And Economic-Statistical Designs Of Several Auxiliary Information Control Charts by Ng Peh, Sang

    Published 2020
    “…The use of auxiliary information (AI) concept in control charts is receiving increasing attention among researchers. …”
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    Thesis
  6. 6

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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    Thesis
  7. 7

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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    Book
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    Improving the synthetic coefficient of variation chart by incorporating side sensitivity by Lee, PingYin

    Published 2024
    “…The control chart is recognized as a crucial technique in Statistical Process Control. …”
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    Thesis
  11. 11

    Computer control of batch process plant (software development) by Safian, Salehudin

    Published 1995
    “…The algorithm has been successful tested using the Non-interacting Liquid Level Control of Three lank System plant models transfer function.…”
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    Student Project
  12. 12
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    Fault diagnostic advisory system using moving-range chart and hazard operability study. by Heng, Han Yann, Ali, Mohamad Wijayanuddin, Kamsah, Mohd Zaki

    Published 2007
    “…Firstly, a plant model was simulated by using commercial HYSYS. PlantTM stimulator. Moving-Range (x-MR) Chart and (HAZOP) study were used to define the causes and consequences of process deviation based on selected parameter for each study node. …”
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    Article
  14. 14

    Fault diagnostic advisory system using moving-range chart and hazard operability study by Heng, Han Yann, Ali, Mohamed Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2007
    “…Firstly, a plant model was simulated by using commercial HYSYS. PlantTM simulator. Moving-Range (x-MR) Chart and HAZOP study were used to define the causes and consequences of process deviation based on selected parameter for each study node. …”
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    Article
  15. 15

    Monitoring the coefficient of variation using a variable sample size EWMA chart by Muhammad, Anis Nabila, Yeong, Wai Chung, Chong, Zhi Lin, Lim, Sok Li, Khoo, Michael Boon Chong

    Published 2018
    “…Subsequently, an optimization algorithm to optimize the performance of the proposed chart is developed. …”
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    Article
  16. 16

    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Saufi, Syahril Ramadhan, Mahmood, Salwa

    Published 2023
    “…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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    Article
  17. 17

    Development of a rule-based fault diagnostic advisory system for precut fractionation column by Heng, Han Yann

    Published 2005
    “…Univariate Statistical Process Control technique (Individual and Moving Range (x-MR) chart) and Hazard and Operability (HAZOP) Study were used for the diagnostic task. …”
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    Thesis
  18. 18

    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Waseem Alwan, Waseem Alwan, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Syahril Ramadhan Saufi, Syahril Ramadhan Saufi, Mahmood, Salwa

    Published 2023
    “…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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    Article
  19. 19

    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Ramadhan Saufi, Syahril, Mahmood, Salwa

    Published 2023
    “…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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    Article
  20. 20

    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Saufi, Syahril Ramadhan, Mahmood, Salwa

    Published 2023
    “…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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    Article