Sazali Yaacob, Prof. Dr.
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This page provides access to research works by Prof. Dr. Sazali Yaacob, former Professor at School of Mechatronic Engineering, Universiti Malaysia Perlis.
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Skills and Expertise: Artificial Intelligence Applications, Control Theory, Acoustic, Engineering, Control Systems Engineering, Signal Processing, Space Sciences, Image and Video Processing
Recent Submissions
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The study of particle filter for satellite angular rate estimation without rate sensor measurement
(EDP Sciences, 2018)This paper studies particle filter algorithm to estimate the angular rate of a satellite without the rate sensor measurements. In this work, the performance of the algorithm is studied in terms of capability to estimate ... -
Objective investigation of vision impairments using single trial pattern reversal visually evoked potentials
(Elsevier Ltd., 2013-07)Visually evoked potentials (VEPs) originate from the occipital cortex and have long been used as a reliable indicator for vision impairments by ophthalmologists. Any abnormalities in the visual pathways of a person can be ... -
Malaysian English accents identification using LPC and formant analysis
(IEEE Conference Publications, 2011-11)In Malaysia, most people speak several varieties of English known as Malaysian English (MalE) and there is no uniform version because of the existence of multi-ethnic population. It is a common scenario that Malaysians ... -
Speaker accent recognition through statistical descriptors of Mel-bands spectral energy and neural network model
(IEEE Conference Publications, 2012-10)Accent recognition is one of the most important topics in automatic speaker and speaker-independent speech recognition (SI-ASR) systems in recent years. The growth of voice-controlled technologies has becoming part of our ... -
Classification of speaker accent using hybrid DWT-LPC features and K-nearest neighbors in ethnically diverse Malaysian English
(IEEE Conference Publications, 2012-12)Accent is a major cause of variability in automatic speaker-independent speech recognition systems. Under certain circumstances, this event introduces unsatisfactory performance of the systems. In order to circumvent this ... -
Feature space reduction in ethnically diverse Malaysian English accents classification
(IEEE Conference Publications, 2013)In this paper we propose a reduced dimensional space of statistical descriptors of mel-bands spectral energy (MBSE) vectors for accent classification of Malaysian English (MalE) speakers caused by diverse ethnics. Principle ... -
Motorbike engine faults diagnosing system using neural network
(IEEE Conference Publications, 2008-12)Monitoring systems for motorbike industry requires high and efficient degree of performance. In recent years, automatic identification and diagnosis of motorbike engine faults has become a very complex and critical task. ... -
Application of frame energy based DCT moments for the damage diagnosis in steel plates using FLNN
(IEEE Conference Publications, 2012-12)This paper discusses the application of frame energy based Discrete Cosine Transformation (DCT) moment features for the detection of damages in steel plates. A simple experimental model is devised to suspend the steel ... -
Steel plate damage diagnosis using probabilistic neural network
(IEEE Conference Publications, 2013-01)This paper discusses the application of frame energy based DFT spectral band features for the detection of damages in steel plates. A simple experimental model is devised to suspend the steel plates in a free-free condition. ... -
In vitro evaluation of finger's hemodynamics for vein graft surveillance using electrical bio-impedance method
(American-Eurasian Network for Scientific Information (AENSI), 2014-03)Electrical bio-impedance measurement has great potential in many biomedical applications including vein graft surveillance. Studies have shown that thrombosis was the major cause of the vein graft failure. The meticulous ... -
Structural steel plate damage detection using non destructive testing, frame energy based statistical features and artificial neural networks
(Elsevier Ltd., 2013)This paper discusses about the detection of damages present in the steel plates using nondestructive vibration testing. A simple experimental model has been developed to hold the steel plate complying with the simply ... -
EEG based detection of conductive and sensorineural hearing loss using artificial neural networks
(Advanced Institute of Convergence IT, 2013-05)In this paper, a simple method has been proposed to distinguish the normal and abnormal hearing subjects (conductive or sensorineural hearing loss) using acoustically stimulated EEG signals. Auditory Evoked Potential (AEP) ... -
An application of finite element modelling to pneumatic artificial muscle
(Science Publications, 2005)The purpose of this article was to introduce and to give an overview of the Pneumatic Artificial Muscles (PAMs) as a whole and to discuss its numerical modelling, using the Finite Element (FE) Method. Thus, more information ... -
Car cabin interior noise classification using temporal composite features and probabilistic neural network model
(Trans Tech Publications Inc., 2014)Determination of vehicle comfort is important because continuous exposure to the noise and vibration leads to health problems for the driver and passengers. In this paper, a vehicle comfort level classification system has ... -
Lifting scheme for human emotion recognition using EEG
(IEEE Conference Publications, 2008-08)In recent years, the need and importance of automatically recognizing emotions from EEG signals has grown with increasing role of brain computer interface applications. The detection of fine grained changes in functional ... -
Emotion recognition from electrocardiogram signals using Hilbert Huang Transform
(IEEE Conference Publications, 2012-10)Equipping robots and computers with emotional intelligence is becoming important in Human-Computer Interaction (HCI). Bio-signal based methods are found to be reliable and accurate than conventional methods as they directly ... -
Emotion detection from QRS complex of ECG signals using hurst exponent for different age groups
(IEEE Conference Publications, 2013-09)Emotion recognition using physiological signals is one of the key research areas in Human Computer Interaction (HCI). In this work, we identify the six basic emotional states (Happiness, sadness, fear, surprise, disgust ... -
Classification of emotional States from electrocardiogram signals: a non-linear approach based on hurst
(BioMed Central, 2013-05)Background: Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) ... -
Human emotional stress assessment through Heart Rate Detection in a customized protocol experiment
(IEEE Conference Publications, 2012-09)Continuous existence of negative emotions (disgust, anger, fear and sad) over a longer period of time induces emotional stress. This emotional stress can be analyzed through physiological signal characteristics such as ... -
FCM clustering of emotional stress using ECG features
(IEEE Conference Publications, 2013-04)Emotional stress refers to the inducement of stress due to the consequence of a continuous experience of negative emotions (sad, anger, fear and disgust). This work aims to investigate the effect of negative emotions in ...
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