Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

0.61

P-Index

This Author published in this journals

All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science

Marina Yusoff

Universiti Teknologi MARA

Author-ID : 2405220

Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 12 Documents Claim Missing Document

Claim Missing Document

Articles

Title

Mel-log energies analysis of authentic audible intrusion activities in a Malaysian forest Amirul Sadikin Md Afendi; Marina Yusoff; Megawati Omar
Bulletin of Electrical Engineering and Informatics Vol 9, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

Wildlife has been endangered due to illegal activities. This requires more effective surveillance measures. Felling timber and poaching are regular illegal activities but challenging to detect. Hence authorities should resort to modern technologies such as employing autonoumous surveillance to stop them. The Malaysian forest audio data were recorded to lay a foundation in initiating a cheaper and practical approach. Hence this paper reports the collection, processing and analysis of audio data in preparation to develop an autonomous sound event detection system. The recording was an emulation of possible illegal activities in a reserved forest. Sounds of chainsaw and hand hatchet cutting tree trunks were taken. It was found that there was a distinct pattern in the Mel-log energies audio feature of the sound, which could be used to identify illegal activities. Thus, it is believed that a detection through audio is a possible approach to be employed as one of the methods to stop illegal activities in the tropical reserve forests like those in Malaysia.

Knots timber detection and classification with C-Support Vector Machine Fakhira Iwani Muhammad Redzuan; Marina Yusoff
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Timber knots recognition is of prime importance to further determine the timber grade. The recognition is normally based on the human expert’s eyes in which can lead to some flaws based on human limitations and weaknesses. The use of X-ray can cause emits radiation and can be dangerous to the workers. This paper addresses the employment of computational methods for knot detection. A pre-processing and feature extraction methods include contrast stretching, median blur and thresholding, gray scale and local binary pattern were used. More than 400 datasets of knot images of the tropical timbers, namely Acacia and Hevea Brasiliensis have been tested using C-support vector machine as a knot classifier. The findings demonstrate different performances for three types of kernel. Linear kernel function outperformed both radial basis function and polynomial kernel functions for Acacia and Hevea Brasiliensis species. Both species classifications using linear kernel have managed to achieve a promising accuracy. Knots classification with the used of support vector machine has shown a promising result to improve the classifier and test with different types of tropical timbers.

Co-Authors Alya Nurizzati Mohd Basir Amirul Sadikin Md Afendi Amirul Sadikin Md Affendi Anis Amalina Othman Fakhira Iwani Muhammad Redzuan Faris Mohd Najib Jasni Mohamad Zain Megawati Omar Mohammed Adam Kunna Azrag Muhamad Amirul Sadikin Md Afendi Norhidayah A Kadir Nurshazwani Muhamad Mahfuz Rozaina Ismail Shahril Anuar Bahari Tao Hai Tuty Asmawaty Abdul Kadir Zainura Idrus Zakiah Ahmad

Title Search

Found 2 Documents Search Journal : Bulletin of Electrical Engineering and Informatics

Abstract

Abstract

Title

Found 2 Documents
Search
Journal : Bulletin of Electrical Engineering and Informatics