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

    Efficient task scheduling strategies using symbiotic organisms search algorithm for cloud computing environment by Sa'ad, Suleiman

    Published 2022
    “…However, the efficiency of the clouds drops as the size of the search space gets larger, like in the case of most metaheuristic optimisation algorithms. …”
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    Thesis
  4. 4

    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
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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
  7. 7

    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
  8. 8

    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
  9. 9

    Land Use Changes in Jeli, Kelantan by Muhammad Firdaus Abdul Karim

    Published 2013
    “…Land use change percentage and urban land expansion index (SI) are selected algorithm in this study. The overall accuracy assessment ranged from 61.39% to 92.05% which is moderate to accurate. …”
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    Undergraduate Final Project Report
  10. 10

    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
  11. 11

    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
  12. 12

    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
  13. 13

    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
  14. 14

    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
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    Task scheduling in cloud computing environment using hybrid of genetic algorithm and naked mole rat algorithm (GA-NMRA) by Mohammad Ozaniezie Onasis

    Published 2022
    “…Task scheduling and resource allocation are essential aspects of cloud computing. This research proposes task scheduling in cloud computing using a hybrid genetic algorithm and naked mole rat algorithm to solve the task scheduling problem. …”
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    Academic Exercise
  17. 17

    Hybrid cryptography algorithm to improve security cloud storage by Abd Almohsen, Inam Razzaq

    Published 2017
    “…To improve secure of data in cloud storage by hybrid three algorithms (AES, ECC and RSA).All the existing algorithms has some sort of problems and issues, this had made us decide to develop a safe, correct ad efficient algorithm for having secured data in cloud storage. …”
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    Thesis
  18. 18

    Multi-objective algorithms for effective resource management in Edge-Fog-Cloud computing by Saif, Faten Ameen Mohammed

    Published 2023
    “…Simulations were conducted to evaluate the proposed algorithms compared to the PSO algorithm, Cloud-Fog Cooperation Scheduling algorithm, and Task offloading algorithm. …”
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    Thesis
  19. 19

    Task scheduling in cloud computing using hybrid genetic algorithm and bald eagle search (GA-BES) by Kamal Khairi Supaprhman

    Published 2022
    “…Task scheduling and resource allocation are essential aspects of cloud computing. This Study proposes task scheduling in cloud computing using a hybrid genetic algorithm, and bald eagle search proposed to solve the task scheduling problem. …”
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    Academic Exercise
  20. 20

    Modified workflow scheduling using hybrid PSO-GA algorithm in cloud computing by Oke, Omotayo Patrick

    Published 2019
    “…The goal of the Hybrid GA-PSO algorithm is to reduce the makespan and cost and balance the load of dependent tasks in cloud computing environments over the heterogonous resources. …”
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    Thesis