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Total records found : 6
Simplified search suggestions : Nazre Abdul Rashid
12018
thesis
Learner's brain Electroencephalogram subbands for Kolb's learning style classification
Nazre Abdul Rashid
Learning has been connected specifically to a human brain whereby brain's capacities such as thinking, short and long term memory are considered among the most critical modalities of learners. On the other hand, Learning Style (LS) had been widely accepted in education domain with the emergence of several LS models. Nevertheless, the models used only questionnaire-based Learning Style Inventory (LSI) in the LS determination process which exposed to inaccuracy. As such, this research proposes a new method whereby Electroencephalogram (EEG) signals are used hand-in-hand with the traditional LSI for Kolb's LS classification establishment The research also aimed to determine the EEG sub-bands that could best classify the Kolb's LS and outline their characteristics. A total of 131 subjects were classified into their particular Kolb's LS of Diverger (n=33), Assimilator (n=36), Converger (n=32) or Accommodator (n=30) using the Kolb's Learning Style Inventory (KLSI) Workbook 3.1 by Haygroup®......

854 hits

22017
article
The current practice of data management of schools and District Education Offices: is there a need for a new approach?
Ubaidullah Nor Hasbiah, Mohamed Zulkifley, Saad Aslina, Hamid Jamilah, Abdul Rashid Nazre, Hashim Mohamadisa, Omar Khan Saira Banu,
2575 hits

32017
article
Slow and fast EEG waves analysis for kolbs learning style classification
Abdul Rashid Nazre, Taib Mohd. Nasir, Lias Sahrim, Sulaiman Norizam, Murat Zunairah,
1201 hits

42019
article
EEG motor imagery applications in brain computer interface based wheelchair control
Nazre bin Abdul Rashid
Principally, this study gives an overview about the Neuronal oscillations appear throughout the nervous system in structures as well as, the range of frequencies of clinical and physiological interests for motor imagery EEG signal. In addition, a brief description about MI paradigm which is also known as movement imagery, which is a mental process through which a person imagines a physical action, such as jumping, or moving hands. In particular, event-related desynchronization (ERD) and synchronization (ERS). Finally, a set of studies have been listed towards highlights the advantages of using BCI Competition dataset which is a public dataset that have been widely used in the analysis of the EEG motor imagery signal methods and technique...

942 hits

52019
article
Cisco packet tracer simulation as effective Pedagogy in computer networking course
Nazre Abdul Rashid
The Computer Networking course commonly taught in mixed mode involving lecture and practical session whereas beside face-to-face theory session, students need to experience hands-on activities in order to appreciate the technology and contents. Nevertheless, the abstraction in Computer Networking course such as the complexity in TCP/IP network layering, the connection and configuration of client and server’s framework, differences in static and dynamic IP address configuration had imposed a great challenge for students to understand and grab the main concept of computer networking technology. As such, an approach of using computer network simulation and visualization tool in teaching and learning Computer Networking course is seen beneficial for educators and students. In this research, computer network simulation software of CISCO Packet Tracer was utilized in Computer Networking (MTN3023) course. Students (N=55) were exposed to CISCO Packet Tracer on which they developed Wide Area .....

744 hits

62020
article
Comparative analysis of machine learning techniques for splitting identifiers within source code
Nazre Abdul Rashid
Feature location is the process of extracting identifiers within source code. In software engineering, it is a usual procedure to upgrade software by adding new features. In order to facilitate this process for the developers, feature location has been proposed to extract the significant components within the source code which are the identifiers. One of the challenging issues that faces the feature location task is handling multi-word identifiers where developers may use different type of separations among the words. Different research studies have used various types of techniques. However, recent studies have showed interest in Machine Learning Techniques (MLTs) due to their substantial performance. With the diversity MLTs, there is a vital demand to identify the most accurate one in terms of splitting the identifiers correctly. Therefore, this study aims to provide a comparative analysis of different MLTs including Naïve Bayes, Support Vector Machine and J48. The dataset used in th.....

477 hits

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