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p-Index From 2021 - 2026
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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics Computer Science and Information Technologies
Mohamad Noor, Noor Maizura
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Multi-priority scheduling algorithm for scientific workflows in cloud Albtoush, Alaa; Yunus, Farizah; Mohamad Noor, Noor Maizura
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.7520

Abstract

The public cloud environment has emerged as a promising platform for exe-cuting scientific workflows. These executions involve leasing virtual machines (VMs) from public services for the duration of the workflow. The structure of the workflows significantly impacts the performance of any proposed scheduling approach. A task within a workflow cannot begin its execution before receiving all the required data from its preceding tasks. In this paper, we introduce a multi-priority scheduling approach for executing workflow tasks in the cloud. The key component of the proposed approach is a mechanism that logically or-ders and groups workflow tasks based on their data dependencies and locality. Using the proposed approach, the number of available VMs influences the num-ber of groups (partitions) obtained. Based on the locality of each group’s tasks, the priority of each group is determined to reduce the overall execution delay and improve VM utilization. As the results demonstrate, the proposed approach achieves a significant reduction in both execution costs and time in most scenar-ios
Visualisation for ontology sense-making: A tree-map based algorithmic approach Vidanage, Kaneeka; Mohamad Noor, Noor Maizura; Mohemad, Rosmayati; Bakar, Zuriana Abu
Computer Science and Information Technologies Vol 2, No 3: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v2i3.p147-157

Abstract

Ontology sense-making or visual comprehension of the ontological schemata and structure are vital for cross-validation purposes of the ontology increment during the process of applied ontology construction. Also, it is important to query the ontology in order to verify the accuracy of the stored knowledge embeddings. This will boost the interactions between domain specialists and ontologists in applied ontology construction processes. Hence existing mechanisms have numerous of deficiencies (discussed in the paper), a new algorithm is proposed in this research to boost the efficiency of usage of tree-maps for effective ontology sense making. Proposed algorithm and prototype are quantitatively and qualitatively assessed for their accuracy and efficacy.
Performance analysis in text clustering using k-means and k-medoids algorithms for Malay crime documents Mohemad, Rosmayati; Mohd Muhait, Nazratul Naziah; Mohamad Noor, Noor Maizura; Othman, Zulaiha Ali
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5014-5026

Abstract

Few studies on text clustering for the Malay language have been conducted due to some limitations that need to be addressed. The purpose of this article is to compare the two clustering algorithms of k-means and k-medoids using Euclidean distance similarity to determine which method is the best for clustering documents. Both algorithms are applied to 1000 documents pertaining to housebreaking crimes involving a variety of different modus operandi. Comparability results indicate that the k-means algorithm performed the best at clustering the relevant documents, with a 78% accuracy rate. K-means clustering also achieves the best performance for cluster evaluation when comparing the average within-cluster distance to the k-medoids algorithm. However, k-medoids perform exceptionally well on the Davis Bouldin index (DBI). Furthermore, the accuracy of k-means is dependent on the number of initial clusters, where the appropriate cluster number can be determined using the elbow method.
Co-Authors Albtoush, Alaa Bakar, Zuriana Abu Mohd Muhait, Nazratul Naziah Mohemad, Rosmayati Othman, Zulaiha Ali Vidanage, Kaneeka Yunus, Farizah