Search Results - ((((canopy algorithm) OR (cloud algorithm))) OR (acs algorithm))

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  1. 1

    Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment by Wang, Kai, Zhou, Jun, Zhang, Wenhai, Zhang, Baohua

    Published 2021
    “…The system uses a LiDAR-IMU tight coupling odometry method to reconstruct a point cloud map of the area surveyed. After using the RANSAC algorithm to remove the map ground, the European clustering algorithm is used for point cloud segmentation. …”
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    Article
  2. 2

    Individual-tree segmentation and extraction based on LiDAR point cloud data by Liu, Xiaofeng, Abdullah, Muhamad Taufik, Mustaffa, Mas Rina, Nasharuddin, Nurul Amelina

    Published 2024
    “…Utilizing LiDAR point cloud data and ground-measured data from 30 plots, we examined the sensitivity of individual tree segmentation to key parameters by varying the grid values of the point cloud distance discriminant clustering algorithm and adjusting the canopy height resolution (CHR) of the watershed algorithm. …”
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  3. 3

    Empowering cloud providers: optimised locust-inspired algorithm for SLA violation mitigation in green cloud computing by Alsaaidah, Yousef A., Muhammed, Abdullah, Ala’anzy, Mohammed Alaa, Othman, Mohamed, Abdullah, Azizol

    Published 2025
    “…It enhances the locust-inspired algorithm by integrating SLA-awareness and adaptive host classification and is evaluated using real workload traces in the CloudSim toolkit. …”
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    Article
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    HSO: A hybrid swarm optimization algorithm for reducing energy consumption in the cloudlets by Hasan, Raed Abdulkareem, Mostafa, A. Mohammed, Salih, Zeyad Hussein, M. A., Ameedeen, Tapus, Nicolae, Mohammed, Muamer N.

    Published 2018
    “…There was also a decrease in the node loss which allowed the optimization algorithm to achieve a minimal overhead on cloud compute resources while still saving energy significantly. …”
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    Article
  6. 6

    Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data by David A. Coomes, Michele Dalponte, Tommaso Jucker, Gregory P. Asner, Lindsay F. Banin, David F.R.P. Burslem, Simon L. Lewis, Reuben Nilus, Oliver L. Phillips, Phua, Mui How, Lan Qie

    Published 2017
    “…We compare the performance of (a) an area-based model developed by Asner and Mascaro (2014), and used primarily in the neotropics hitherto, with (b) a tree centric approach that uses a new algorithm (itcSegment) to locate trees within the ALS canopy height model, measures their heights and crown widths, and calculates biomass from these dimensions. …”
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    Article
  7. 7

    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

    Published 2020
    “…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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    Thesis
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    Solar power inverter by Mohd Hafizuddin, Mohamed Ariffin

    Published 2013
    “…For systems with battery energy storage, the controller can control the charging as well as switch over to battery power once the sun sets or cloud cover reduces the PV output power. The controller executes the very precise algorithms required to invert the DC voltage generated by the solar module into AC This controller is programmed to perform the control loops necessary for all the power management functions necessary including DC/DC and DC/AC.…”
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    Undergraduates Project Papers
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    Detecting canopy openings in logged-over forests: a multi-classifier analysis of PlanetScope imagery by Mawlidan, Nurmala, Ismail, Mohd Hasmadi, Gandaseca, Seca, ., Rahmawaty, Yaakub, Nur Faziera

    Published 2024
    “…Both SVM and OBIA surpassed the accuracy threshold, with SVM being the most effective in detecting and extracting canopy openings in dense forests. Results demonstrated the potential of PlanetSope imagery and advanced classification algorithms to detect canopy openings in logged-over forests. …”
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    Article
  12. 12

    ESS-IoT: The Smart Waste Management System for General Household by Wong S.Y., Han H., Cheng K.M., Koo A.C., Yussof S.

    Published 2024
    “…The results show that CNN is the better classification algorithm between the two. Future work proposes the research extension by introducing an incentive mechanism to motivate the household communities using a cloud-based competition platform incorporated with the ESS-IoT system. � Universiti Putra Malaysia Press.…”
    Article
  13. 13

    Photogrammetric unmanned aerial vehicle for digital terrain model estimation under oil palm tree canopy area / Suzanah Abdullah by Abdullah, Suzanah

    Published 2021
    “…It was found that WS algorithm recorded the lower RMSE value of 2.824m at 40m flying height, IWS algorithm obtained a lower RMSE value of 2.879m at 80m flying height, OBIA and SG algorithms obtained a lower RMSE value of 2.246m and 2.182m respectively at 100m flying height. …”
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    Thesis
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    Performance-aware cost-effective brokering and load balancing algorithms for data center in large scale cloud computing by Naha, Ranesh Kumar

    Published 2015
    “…Proposed cloud brokering algorithms works with different types of cloud provider and deal with various user requirements. …”
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    Thesis
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    Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing by Parmesivan, Yuganes, Hasan, Sazlinah, Muhammed, Abdullah

    Published 2018
    “…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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    Article
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    A priority based job scheduling algorithm in cloud computing by Shamsollah, Ghanbari, Othman, Mohamed

    Published 2012
    “…Job scheduling algorithms is one of the most challenging theoretical issues in the cloud computing area. …”
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    Conference or Workshop Item
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    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm by Muhammad Syahril Mohamad Sainal

    Published 2022
    “…Furthermore, CloudSim simulator will be used to evaluate the performance of this algorithm. …”
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    Academic Exercise
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    Tag clouds algorithm with the inclusion of personality traits by Ahmad Affandi, Supli

    Published 2015
    “…Furthermore, the algorithm to generate tag cloud visualization based on personality traits has not been explored. …”
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    Thesis
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    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO) by Mohd Erwan Mazalan

    Published 2022
    “…In this project, Genetic Algorithms (GA) is combine Moth Flame Optimization (MFO) to improve the cloud computing environment. …”
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    Academic Exercise