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  1. 1
    RED, GRED, AGRED congestion control algorithms in heterogeneous traffic types

    RED, GRED, AGRED congestion control algorithms in heterogeneous traffic types by Seifaddini, Omid, Abdullah, Azizol, Vosough, Hamid

    Published 2013
    “…The performance metric used to show the analysis of these algorithms with mentioned distributions is Packet Loss (Pl).Results of simulation show that each algorithm performed a fair dropping of data packets without considering of their types.…”
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  2. 2
    Red, gred, agred congestion control algorithms in heterogeneous traffic types

    Red, gred, agred congestion control algorithms in heterogeneous traffic types by Seifaddini, Omid, Abdullah, Azizol, Vosough, Hamid

    Published 2013
    “…The performance metric used to show the analysis of these algorithms with mentioned distributions is Packet Loss (Pl). …”
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  3. 3
    Performance Enhancement of Routing Protocols in Mobile Wireless Ad-Hoc Networks Using Fuzzy Reasoning Algorithm

    Performance Enhancement of Routing Protocols in Mobile Wireless Ad-Hoc Networks Using Fuzzy Reasoning Algorithm by Natsheh, Essam Fathi

    Published 2006
    “…Finally, in the last method fuzzy reasoning is used for network congestion estimation and estimating time to start dropping incoming packets. …”
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  4. 4
    On the delay and link utilization with the new-additive increase multiplicative decrease congestion avoidance and control algorithm

    On the delay and link utilization with the new-additive increase multiplicative decrease congestion avoidance and control algorithm by Jasem, Hayder Natiq, Ahmad Zulkarnain, Zuriati, Othman, Mohamed, Subramaniam, Shamala

    Published 2010
    “…We will use the DropTail mechanism as the active queue management mechanism (AQM) in the bottleneck router. …”
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  5. 5
    Performance study of large block forward error correction with random early detection queue policy

    Performance study of large block forward error correction with random early detection queue policy by Almomani, Omar, Ghazali, Osman, Hassan, Suhaidi

    Published 2009
    “…FEC is a technique that uses redundant packet to reconstruct the dropped packet, while RED is an active queue management algorithm. …”
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  6. 6
    The delay with new-additive increase multiplicative decrease congestion avoidance and control algorithm.

    The delay with new-additive increase multiplicative decrease congestion avoidance and control algorithm. by Jasem, Hayder Natiq, Ahmad Zukarnain, Zuriati, Mohamed, Othman, Subramaniam, Shamala

    Published 2010
    “…And we will use the Drop tail mechanism as Active Queue Management (AQM) in the bottleneck router. …”
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  7. 7
    A simulation study of a new rate-and-queue-based active queue management algorithm

    A simulation study of a new rate-and-queue-based active queue management algorithm by Ali Asghar, Jomah Adham, Razman, Mat Tahar

    Published 2012
    “…In order to enhance quality of service (QoS), active queue management (AQM) algorithms are frequently employed due to their efficiency in congestion avoidance as well as the differentiated forwarding of packets. …”
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  8. 8
    Traffic scheduling and link sharing mechanisms for controlled load service / Chin Yun Choong

    Traffic scheduling and link sharing mechanisms for controlled load service / Chin Yun Choong by Chin , Yun Choong

    Published 2000
    “…We expect the number of dropped packets will decrease especially during congestion time when the "borrow" mechanism is activated. …”
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  9. 9
    Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm

    Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm by Mohd Redzuan, Ahmad, Ismail, Musirin, M. M., Othman

    Published 2014
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  10. 10
    Quantitative study of iterative reconstruction algorithms of spect/ct in bone scan: a clinical and phantom study

    Quantitative study of iterative reconstruction algorithms of spect/ct in bone scan: a clinical and phantom study by Hao, Lau Lik

    Published 2024
    “…For all algorithms, increasing the iteration numbers elevated RC, SUV, and noise, while SNR dropped. …”
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  11. 11
    Investigation of maximum power point tracking (MPPT) for active cooling mono-crystalline photovoltaic panel using fuzzy logic controller

    Investigation of maximum power point tracking (MPPT) for active cooling mono-crystalline photovoltaic panel using fuzzy logic controller by Nurul Afiqah, Zainal

    Published 2017
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  12. 12
    A multi-control vehicle-to-grid charger with bi-directional active and reactive power capabilities for power grid support

    A multi-control vehicle-to-grid charger with bi-directional active and reactive power capabilities for power grid support by Tan K.M., Padmanaban S., Yong J.Y., Ramachandaramurthy V.K.

    Published 2023
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  13. 13
    Adaptive unified neural network for dynamic power quality compensation

    Adaptive unified neural network for dynamic power quality compensation by Ghazanfarpour, Behzad, Mohd Radzi, Mohd Amran, Mariun, Norman, Shoorangiz, Reza

    Published 2013
    “…For compensating the fault, another controller plant is implemented that uses Levenberg-Marquardt backpropagation algorithm. …”
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  14. 14
    Hybrid artificial intelligent algorithm for call admission control in WCDMA mobile network

    Hybrid artificial intelligent algorithm for call admission control in WCDMA mobile network by Tee Y.K., Tiong S.K., Johnny K.S.P., Yeoh E.C.

    Published 2023
    “…The proposed algorithm, support vector regression assists genetic algorithm (SVRaGA) was tested in a dynamic WCDMA mobile network simulator. …”
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  15. 15
    Development of a scalable video compression algorithm

    Development of a scalable video compression algorithm by Khalifa, Othman Omran, Issa, Sinzobakwira, Olanweraju, Rashidah Funke, Al Khazmi, El Mahdi A

    Published 2012
    “…In this paper a rate distortion optimized video frame dropping strategy which can be applied on active network nodes during high traffic intensity for H.264/AVC was developed. …”
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  16. 16
    Machine learning algorithms for early predicting dropout student online learning

    Machine learning algorithms for early predicting dropout student online learning by Dewi, Meta Amalya, Kurniadi, Felix Indra, Murad, Dina Fitria, Rabiha, Sucianna Ghadati, Awanis, Romli

    Published 2023
    “…This is one of the causes of the high dropout rate among online learning students, so it is very important for lecturers and administrators to support students in a timely manner to avoid the risk of dropping out. This study uses access log data recorded in the LMS and student statistical information and calculated data and aims to present a suitable predictive algorithm for dropout early prediction systems for online learning students using machine learning. …”
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  17. 17
    Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection

    Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection by Ahmed Khan, Fazeel, Abubakar, Adamu

    Published 2024
    “…The data was gathered using real-time packet capturing tools which were then processed and moved with model development using different deep learning algorithms such as, LSTM, MLP, RNN and Autoencoders. …”
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  18. 18
    Analysis of vehicular traffic flow of main road and alternative road in Kuala Terengganu / Nur Aribah Farzana Arifen & Nur Aiman Salsabila Hashim

    Analysis of vehicular traffic flow of main road and alternative road in Kuala Terengganu / Nur Aribah Farzana Arifen & Nur Aiman Salsabila Hashim by Arifen, Nur Aribah Farzana, Hashim, Nur Aiman Salsabila

    Published 2019
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  19. 19
    Indoor occupancy detection using machine learning and environmental sensors / Akindele Segun Afolabi ... [et al.]

    Indoor occupancy detection using machine learning and environmental sensors / Akindele Segun Afolabi ... [et al.] by Afolabi, Akindele Segun, Akinola, Olubunmi Adewale, Odetoye, Oyinlolu Ayomidotun, Adetiba, Emmanuel

    Published 2025
    “…In this paper, we experimentally determined the Machine Learning (ML) models that are most robust for use in indoor occupancy detection. This is important because the activities of human subjects in an ML environment are capable of disrupting the data available to some deployed ML models, which might cause the performance of such models to drop. …”
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  20. 20
    Development of a lower-extremities exoskeleton for postural-sway in sit-to-stand movement

    Development of a lower-extremities exoskeleton for postural-sway in sit-to-stand movement by Lee, Jun Han

    Published 2025
    “…The system integrates an ESP32 microcontroller, IMU-based sway detection, and a threshold-based control algorithm for real time actuation. The fully assembled prototype was evaluated in 15 subjects across varying stance (normal, tandem) and visual (eyes open/closed) conditions using surface electromyography (sEMG) and centre of pressure (CoP) metrics. …”
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