Search Results - (( data replication methods algorithm ) OR ( data realization _ algorithm ))

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  1. 1

    Dynamic replication algorithm in data grid: Survey by K. Madi, Mohammed, Hassan, Suhaidi

    Published 2008
    “…For improving the performance of file accesses and to ease the sharing amongst distributed collaboration, such a system needs replication services. Data replication is a common method used to improve the performance of data access in distributed systems. …”
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    Book Section
  2. 2

    Enhanced replication strategy with balanced quorum technique and data center selection method in cloud environment by Mohd Ali, Fazlina

    Published 2022
    “…In order to mitigate the issues, ‘cloud data replication’ is commonly implemented for better data performance and promising business continuity. …”
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    Thesis
  3. 3

    Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

    Published 2011
    “…The motivation of implementation is to make sure the data replication is easy to maintain and cost effective. …”
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    Thesis
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    Balanced Stochastic Realization Algorithm For Development Of Rainfall Model by Azhari, Fahimy

    Published 2014
    “…In this research, Balanced Stochastic Realization (BSR) subspace algorithm is used to develop a rainfall model for Malaysia. …”
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    Thesis
  7. 7

    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

    Published 2014
    “…The success evaluation of data mining classification algorithms have been realized through the data mining programs Weka and RapidMiner. …”
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    Article
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    Relationship based replication algorithm for data grid by Yusof, Yuhanis

    Published 2014
    “…The Relationship based Replication algorithm aims to improve the Data Grid performance by reducing the job execution time, bandwidth and storage usage.The RBR was realized using a network simulation (OptorSim) and experiment results revealed that it offers better performance than existing replication algorithms.…”
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    Monograph
  10. 10

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…To address this issue, various data pre-processing methods called Feature Selection (FS) techniques have been presented in the literature. …”
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    Article
  11. 11

    Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data by Fanos, Ali Mutar, Pradhan, Biswajeet, Mansor, Shattri, Md Yusoff, Zainuddin, Abdullah, Ahmad Fikri, Jung, Hyung Sup

    Published 2019
    “…In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.…”
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    Article
  12. 12

    Enhanced Model Compression for Lipreading Recognition based on Knowledge Distillation Algorithm by Qianru, Lu, Kuryati, Kipli, Tengku Mohd Afendi, Zulcaffle, Yuan, Liu, Xiangju, Liu, Bo, Wang

    Published 2025
    “…However, Chinese language features are rich and fuzzy, and the training optimization of lip-reading model requires high GPU computation and storage, so it is difficult to realize large-scale application. Therefore, three knowledge distillation compression algorithms are proposed in this paper: Three different knowledge distillation compression algorithms, an offline model compression algorithm based on multi-feature transfer (MTOF), an online model compression algorithm based on adversarial learning (ALON), and an online model compression algorithm based on consistent regularization(CRON) to complete the compression of the Chinese character sequence output by the model. …”
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    Article
  13. 13

    Sentiment mining using immune network algorithm /Raja Muhammad Hafiz Raja Kamarudin by Raja Kamarudin, Raja Muhammad Hafiz

    Published 2012
    “…This research tries to utilize biological-inspired computing algorithm, Immune Network algorithm, in this sentiment analysis field. …”
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    Thesis
  14. 14

    Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning by Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping

    Published 2019
    “…Moreover, generated topological networks cannot represent the distribution of data. In contrast, the proposed algorithm realizes a stable computation and reduces the number of parameters compared to existing algorithms. …”
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    Article
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    Implementation Of FPGA Based Encryption Chip Using VHD - Data Encryption Standard (DES) Algorithm by Lim, Mui Liang

    Published 2006
    “…There are many researchers used Data Encryption Standard (DES) Algorithm to implement in FPGAs. …”
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    Monograph
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    Development of decentralized data fusion algorithm with optimized kalman filter. by Quadri, Sayed Abulhasan

    Published 2016
    “…In all the applications, various data fusion algorithms such as Kalman filter algorithm, factor analysis (FA) algorithm and the proposed QR-FA algorithm are compared on basis of estimation error. …”
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    Thesis
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    A big data prediction framework for weather forecast using MapReduce algorithm by Khalid, Adam, Mazlina, Abdul Majid, Fakherldin, Mohammed Adam Ibrahim, Jasni, Mohamad Zain

    Published 2017
    “…The process of weather forecasting is developing as the effect of advancement in technology right from the realization of increasing size of data, Weather forecasting was found to be based on big data. …”
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    Article
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    Two objectives big data task scheduling using swarm intelligence in cloud computing by Diallo, Laouratou, Hassan Abdalla Hashim, Aisha, Olanrewaju, Rashidah Funke, Islam, Shayla, Zarir, Abdullah Ahmad

    Published 2016
    “…However, these scheduling algorithms vary in term of their performance and most of these traditional and simple scheduling algorithms may not be efficient for large scale data. …”
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    Article