Search Results - (( variable detection bayes algorithm ) OR ( java application customization algorithm ))

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  1. 1
    An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection

    An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

    Published 2018
    “…Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. …”
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  2. 2
    Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach

    Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach by Bahadar A., Kanthasamy R., Sait H.H., Zwawi M., Algarni M., Ayodele B.V., Cheng C.K., Wei L.J.

    Published 2023
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  3. 3
    An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach

    An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach by Mohamed Yassin, Warusia

    Published 2015
    “…Therefore, Statisticalbased Packet Header Anomaly Detection (SPHAD) and a hybridized Naive Bayes and Random Forest classifier (NB+RF) are considered for the ADS, and Signature-based Packet Header Intrusion Detection (SPHID) is proposed as the SDS. …”
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  4. 4
    Enhancing obfuscation technique for protecting source code against software reverse engineering

    Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

    Published 2019
    “…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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  5. 5
    Computer-aided diagnosis of diabetic subjects by heart rate variability signals using discrete wavelet transform method

    Computer-aided diagnosis of diabetic subjects by heart rate variability signals using discrete wavelet transform method by Acharya, U.R., Sudarshan, V.K., Ghista, D.N., Lim, W.J.E., Molinari, F., Sankaranarayanan, M.

    Published 2015
    “…These features are ranked by using various ranking methods, namely, Bhattacharyya space algorithm, t-test, Wilcoxon test, Receiver Operating Curve (ROC) and entropy. …”
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  6. 6
    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis

    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

    Published 2019
    “…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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  7. 7
    Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease

    Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

    Published 2021
    “…Infected palms are asymptomatic throughout the disease's early stages, making disease detection challenging. The survival of affected trees must detect BSR at the mild infected (T1) stage. …”
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  8. 8
    Design & Development of a Robotic System Using LEGO Mindstorm

    Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

    Published 2006
    “…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. …”
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  9. 9
    Feature Ranking Techniques For 3D ATS Drug Molecular Structure Identification

    Feature Ranking Techniques For 3D ATS Drug Molecular Structure Identification by Saw, Yee Ching

    Published 2018
    “…Six feature ranking techniques were used: Information Gain (IG), Gain Ratio (GR), Symmetrical Uncertainty (SU), Support vector machine based recursive feature elimination (SVM-RFE), and Variable Importance based random forest (VI-RF). The selected feature subset by each of the selected feature ranking technique were run through five different popular classifiers: Random forest (RF), Naïve Bayes (NB), IBK, Sequential Minimal Optimization (SMO), J48, and their performances were analyzed and compared. …”
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