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  1. 1
    Detection of black hole attacks in mobile ad hoc networks via HSA-CBDS method

    Detection of black hole attacks in mobile ad hoc networks via HSA-CBDS method by Fahad, Ahmed Mohammed, Ahmed, Abdulghani Ali, Alghushami, Abdullah H., Alani, Sammer

    Published 2019
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  2. 2
    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model

    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model by Elfaki, Faiz. A. M.

    Published 2000
    “…These estimates were then compared to the Newton-Raphson iteration method. A generated data where the failure times were taken as exponentially distributed was used to further compare these two methods of estimation. …”
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  3. 3
    Hybrid Balance Artificial Potential Field Navigation System For An Autonomous Surface Vessel In Riverine Environment

    Hybrid Balance Artificial Potential Field Navigation System For An Autonomous Surface Vessel In Riverine Environment by Jianhong, Mei

    Published 2019
    “…The Euclidean distances of detected lines from ground truth are used to compare the accuracy of the proposed method. …”
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  4. 4
    Friendship Degree and Tenth Man Strategy: A new method for differentiating between erroneous readings and true events in wireless sensor networks

    Friendship Degree and Tenth Man Strategy: A new method for differentiating between erroneous readings and true events in wireless sensor networks by Adday, Ghaihab Hassan, Subramaniam, Shamala K., Zukarnain, Zuriati Ahmad, Samian, Normalia

    Published 2023
    “…The results were compared to the baseline algorithm, highlighting key parameters like false alarms and event detection accuracy. …”
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  5. 5
    Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis

    Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis by Mohamed Elfaki, Faiz Ahmed

    Published 2004
    “…The x chart, R chart and Cp, and Cpk are examined for the possibility of being used to detect the state of control of the covariates in the two competing risks models (Cox’s with Weibull distribution (PHW2) and modification of weighted score function (MW)). …”
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  6. 6
    The summer heat of cryptojacking season : Detecting cryptojacking using heatmap and fuzzy

    The summer heat of cryptojacking season : Detecting cryptojacking using heatmap and fuzzy by Ahmad Firdaus, Zainal Abidin, Aldharhani, Ghassan Saleh, Zahian, Ismail, Mohd Faizal, Ab Razak

    Published 2022
    “…We utilised The Fuzzy Lattice Reasoning (FLR) classifier for classification algorithms in machine learning. This experiment utilised actual cryptojacking samples and achieved a 100 percent detection accuracy rate in simulation.…”
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  7. 7
    Rockfall hazard assessment based on airborne laser scanning data and GIS in tropical region

    Rockfall hazard assessment based on airborne laser scanning data and GIS in tropical region by Fanos, Ali Mutar

    Published 2016
    “…In this study, rockfall source areas were identified using multi-criteria method based on DEM derivates, terrain type or land use/cover (LULC) and high spatial resolution aerial photo (13cm). …”
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  8. 8
    Diagnosis of vocal fold pathology using time-domain features and systole activated neural network

    Diagnosis of vocal fold pathology using time-domain features and systole activated neural network by Paulraj, Murugesa Pandiyan, Prof. Madya, Sazali, Yaacob, Prof. Dr., Hariharan, M.

    Published 2010
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  9. 9
    An efficient trust-based decision-making approach for WSNs: Machine learning oriented approach

    An efficient trust-based decision-making approach for WSNs: Machine learning oriented approach by Khan, T., Singh, K., Shariq, M., Ahmad, K., Savita, K.S., Ahmadian, A., Salahshour, S., Conti, M.

    Published 2023
    “…Moreover, the projected trust model (ETDMA) integrate direct communication trust and indirect trust with the help of a logical time window that periodically records the trustworthy and suspicious interactions. Simulation experiments exhibit the effectiveness of the proposed trust evaluation method in terms of change in trust values, malicious nodes detection (94), FNR (0.9), F1-Score (0.6), and accuracy (92) in the presence of 50 malicious nodes. …”
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  10. 10
    Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System

    Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System by Al-Hameli, Bassam Abdo, Alsewari, Abdulrahman A., Alraddadi, Abdulaziz Saleh, Aldhaqm, Arafat

    Published 2021
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  11. 11
    An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan

    An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan by Ullah, S., Daud, H., Dass, S.C., Hadi, F.-T., Khalil, A.

    Published 2018
    “…The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with no restriction on the distribution and quality of the data, and has shown some promising advantages over the state-of-the-art methods. …”
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  12. 12
    An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan

    An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan by Ullah, S., Daud, H., Dass, S.C., Hadi, F.-T., Khalil, A.

    Published 2018
    “…The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with no restriction on the distribution and quality of the data, and has shown some promising advantages over the state-of-the-art methods. …”
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  13. 13
    1D Multigrid Solver For Finite Element Method

    1D Multigrid Solver For Finite Element Method by Azhar, Mohamad Amiruddin

    Published 2022
    “…The new algorithm also has been tested using time simulation. …”
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  14. 14
    Unified framework for spam detection and risk assessment in short message communication media / Adewole Kayode Sakariyah

    Unified framework for spam detection and risk assessment in short message communication media / Adewole Kayode Sakariyah by Adewole Kayode, Sakariyah

    Published 2018
    “…There are hundreds of published works related to spam message and spam account detection that aim to identify effective detection methods. …”
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  15. 15
    Unsupervised Anomaly Detection with Unlabeled Data Using Clustering

    Unsupervised Anomaly Detection with Unlabeled Data Using Clustering by Chimphlee, Witcha, Abdullah, Abdul Hanan, Md. Sap, Mohd. Noor

    Published 2005
    “…We present a clustering-based intrusion detection algorithm, unsupervised anomaly detection, which trains on unlabeled data in order to detect new intrusions. …”
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  16. 16
    Slope inspection system using image processed by machine learning algorithm to determine risk of slope failure

    Slope inspection system using image processed by machine learning algorithm to determine risk of slope failure by Mat Shukor, S. H., Abdul Hamid, Syamsul Bahrin, Kasim, N., Ab. Moin, Z.

    Published 2020
    “…The conventional method is inefficient and time-consuming. In this paper, the potential of a machine-learning algorithm to improve the conventional approach in detecting the hazard in a landslide is discussed. …”
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  17. 17
    Metacarpal phantom radiograph edge detection using genetic algorithm gradient based genotype / Norharyati Md Ariff

    Metacarpal phantom radiograph edge detection using genetic algorithm gradient based genotype / Norharyati Md Ariff by Md Ariff, Norharyati

    Published 2007
    “…For the image segmentation, genetic algorithm are use to segment the bone image and it is a new method that applies in the image processing field. …”
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  18. 18
    Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim

    Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim by Masmuhallim, Anis Athirah

    Published 2024
    “…The objectives of this project are to study the requirement of the Naive Bayes algorithm in Mobile Banking Trojan detection, to develop a webbased detection system for Mobile Banking Trojan using Naive Bayes, and to evaluate the performance and accuracy of the Naive Bayes algorithm in the Mobile Banking Trojan detection. …”
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  19. 19
    Slope inspection system: using image processed by machine learning algorithm to determine risk of slope failure

    Slope inspection system: using image processed by machine learning algorithm to determine risk of slope failure by Mat Shukor, Sabril Haziq, Syamsul Bahrin, Abdul Hamid, Kasim, Norhidayu, Ab. Moin, Zuraidah

    Published 2020
    “…The conventional method is inefficient and time-consuming. In this paper, the potential of a machine-learning algorithm to improve the conventional approach in detecting the hazard in a landslide is discussed. …”
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  20. 20
    Efficient Sequential and Parallel Routing Algorithms in Optical Multistage Interconnection Network

    Efficient Sequential and Parallel Routing Algorithms in Optical Multistage Interconnection Network by Abduh Kaid, Monir Abdullah

    Published 2005
    “…This routing problem is an NPhard problem. Many algorithms are designed by many researchers to perform this routing such as window method, sequential algorithm, degree-descending algorithm, simulated annealing algorithm, genetic algorithm and ant colony algorithm.This thesis explores two approaches, sequential and parallel approaches. …”
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