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  1. 1

    Whole brain radiation therapy verification using 2D gamma analysis method by Zainodin, Nik Nurul Afina Wan

    Published 2020
    “…The comparison between the PB and CC algorithms in the TPS calculation showed that the dose distribution using the PB algorithm gave a higher maximum and mean dose to the PTV compared to the CC algorithm by 0.15% and 0.1%. …”
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    Thesis
  2. 2

    EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method by Khosropanah, Pegah

    Published 2018
    “…The accuracy of ESL depends on all the stages of data processing including: head model reconstruction, signal pre-processing and inverse solution. Therefore, a standardized algorithm with less supervision is desired to utilize ESL for pre-surgical evaluation. …”
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    Thesis
  3. 3

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…The DPA-EHD is further modified by utilizing the pipelining parallelism to reduce the computing iterations and named as data parallel and pipelining algorithm (DPPA-EHD). To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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    Thesis
  4. 4

    Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

    Published 2022
    “…Six machine learning algorithms were applied and compared based on the classification evaluation methods. …”
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    Final Year Project / Dissertation / Thesis
  5. 5

    A Study of Automated Essay Scoring Frameworks on Evaluating Malaysian University English Test Essays Based on Syntactic and Semantic Features by Chun Then, Lim

    Published 2023
    “…To overcome the problem of imbalanced grade distribution, a resampling method called Synthetic Minority Oversampling Technique (SMOTE) is applied to the dataset to study the impact of the resampling method on the performance of the AES framework. …”
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    Thesis
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  8. 8

    Instance matching framework for heterogeneous semantic web content over linked data environment by Mansir, Abubakar

    Published 2021
    “…The output of each algorithm is evaluated, the results have shown that each algorithm performs well and outperforms the existing algorithms on all test cases in terms better output generation and effective handling of heterogeneity from different domains, which is a necessary concern in all data-intensive problems. …”
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    Thesis
  9. 9

    Uncertainty estimation for improving accuracy of non-rigid registration in cardiac images by Mazaheri, Samaneh, Sulaiman, Puteri Suhaiza, Wirza, Rahmita, Dimon, Mohd Zamrin, Khalid, Fatimah, Tayebi, Rohollah Moosavi

    Published 2015
    “…In other words, uncertainty estimation is used to evaluate the registration algorithm performance which integrates intensity-based and feature-based methods. …”
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    Book Section
  10. 10

    Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

    Published 2024
    “…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”
    Article
  11. 11

    Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti by Abd Mukti, Shahrul Nizan

    Published 2022
    “…The most significant classifier algorithms to distinguish a pothole defect is Maximum likelihood with 29 over 40 band combination win rate. …”
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    Thesis
  12. 12

    Automated detection of microaneurysm for fundus images by Norhasmira, Mohammad, Zaid, Omar, Eko, Supriyanto, Alexander, Dietzel, Jens, Haueisen

    Published 2016
    “…Thus, the objectives of this study are to develop an automated algorithm to perform early detection of MA presence in fundus images, and to evaluate the performance of the proposed system design by evaluating the accuracy of the segmented MA. …”
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    Proceeding
  13. 13

    An enhanced synthetic oversampling framework with self-supervised contrastive learning for multi-class image imbalance by Xiaoling, Gao

    Published 2025
    “…The second contribution is the introduction of the Clustering and Nearest Centroid Neighbour-based Synthetic Minority Oversampling (CLNCN-SMOTE) algorithm to resolve multi-class imbalance. The algorithm is an enhancement of traditional K-means SMOTE that incorporates a nearest centroid neighbour strategy. …”
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    Thesis
  14. 14

    Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream by Abdulateef, Alaa Fareed

    Published 2023
    “…The results indicate that the AGMB algorithm outperformed existing benchmark algorithms in terms of predefined evaluation criteria with an overall 72% accuracy compared to benchmark algorithms which is 11 % only. …”
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    Thesis
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    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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    Thesis
  17. 17

    Block based low complexity iterative QR precoder structure for Massive MIMO by Mok, Li Suet

    Published 2021
    “…In this thesis, we also study and evaluate different conventional linear pre-coding schemes as well as how they relate to optimal structure of the solution which maximize the system performances. …”
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    Thesis
  18. 18

    Evaluation of sparsifying algorithms for speech signals by Kassim, Liban A., Khalifa, Othman Omran, Gunawan, Teddy Surya

    Published 2012
    “…Sparsity is important also in speech compression and coding, where the signal can be compressed in pre-processing stages. It leads to efficient and robust methods for compression, detection denoising and signal separation. …”
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    Proceeding Paper
  19. 19

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…Finally, the effectiveness of the algorithm is evaluated based on the accuracy performance. …”
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    Article
  20. 20

    Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons by Yaseen, Zaher Mundher, Fu, Minglei, Wang, Chen, Mohtar, Wan Hanna Melini Wan, Deo, Ravinesh C., El-Shafie, Ahmed

    Published 2018
    “…In this study, the uncertainty and nonstationary characteristics of streamflow data has been treated using a set of coupled data pre-processing methods before being considered as input for an artificial neural network algorithm namely; rolling mechanism (RM) and grey models (GM). …”
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    Article