R
Rusli Abdullah
Researcher at Universiti Putra Malaysia
Publications - 221
Citations - 2137
Rusli Abdullah is an academic researcher from Universiti Putra Malaysia. The author has contributed to research in topics: Personal knowledge management & Domain knowledge. The author has an hindex of 20, co-authored 209 publications receiving 1630 citations. Previous affiliations of Rusli Abdullah include Information Technology University & UCSI University.
Papers
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Journal ArticleDOI
Improving Dynamic Knowledge Movements with a Knowledge-Based Framework during Conceptual Design of a Green Building Project
Zohreh Pourzolfaghar,Rahinah Ibrahim,Rusli Abdullah,Nor Mariah Adam,Abang Abdullah Abang Ali +4 more
TL;DR: The contribution of this study is developing a technique for capturing tacit knowledge during the conceptual design process that leads to an improvement in knowledge movements during the architectural conceptual design stage.
Journal ArticleDOI
A framework of collaborative knowledge management system in open source software development environment.
TL;DR: The proposed KMS model is envisaged to allow OSS Community-of-Practice to share the OSS knowledge for the whole SDLC from the planning phase until the maintenance phase.
Proceedings ArticleDOI
Security framework of cloud data storage based on Multi Agent system architecture - A pilot study
TL;DR: A security framework based on MAS architecture to facilitate confidentiality, correctness assurance, availability and integrity of collaborative cloud data storage (CDS) environment is proposed and a pilot study is conducted using a questionnaire survey.
Book ChapterDOI
Towards New Data Access Control Technique Based on Multi Agent System Architecture for Cloud Computing
TL;DR: The proposed Multi-Agent System (MAS) architecture consists of two agents: Cloud Service Provider Agent (CSPA) and Cloud Data Confidentiality Agent (CDConA), which provides a graphical interface to the cloud user that facilitates the access to the services offered by the system.
Journal ArticleDOI
Optical Character Recognition for Quranic Image Similarity Matching
Faiz Alotaibi,Muhamad Taufik Abdullah,Rusli Abdullah,Rahmita Wirza O. K. Rahmat,Ibrahim Abaker Targio Hashem,Arun Kumar Sangaiah +5 more
TL;DR: The result of the proposed method is compared with the standard Mushaf al Madinah benchmark to find similarities that match with texts of the Holy Quran and the obtained accuracy was superior to the other tested K-nearest neighbor (knn) algorithm and published results in the literature.