Raja Mohd Kamil Raja Ahmad

Non-invasive and in vivo assessment of osteoarthritic articular cartilage: a review on MRI investigations

Early detection of knee osteoarthritis (OA) is of great interest to orthopaedic surgeons, rheumatologists, radiologists, and researchers because it would allow physicians to provide patients with treatments and advice to slow the onset or progression of the disease. Early detection can be achieved by identifying early changes in selected features of degenerative articular cartilage (AC) using non-invasive imaging modalities. Magnetic resonance imaging (MRI) is becoming the standard for assessment of OA. The aim of this paper was to review the influence of MRI on the selection, detection, and measurement of AC features associated with early OA. Our review of the literature indicates that the changes associated with early OA are in cartilage thickness, cartilage volume, cartilage water content, and proteoglycan content that can be accurately, consistently, and non-invasively measured using MRI. Choosing an MR pulse sequence that provides the capability to assess cartilage physiology and morphology in a single acquisition and advanced multi-nuclei MRI is desirable. The results of the review indicate that using an ultra-high magnetic strength, MR imager does not affect early OA detection. In conclusion, MRI is currently the most suitable modality for early detection of knee OA, and future research should focus on the quantitative evaluation of early OA features using advances in MR hardware, software, and data processing with sophisticated image/pattern recognition techniques.

Modeling and Eigenfrequency Analysis of Sound-Structure Interaction in a Rectangular Enclosure with Finite Element Method

Vibration of structures due to external sound is one of the main causes of interior noise in cavities like automobile, aircraft, and rotorcraft, which disturb the comfort of passengers. Accurate modelling of such phenomena is required in eigenfrequency analysis and in designing an active noise control system to reduce the interior noise. In this paper, the effect of periodic noise travelling into a rectangular enclosure is investigated with finite element method (FEM) using COMSOL Multiphysics software. The periodic acoustic wave is generated by a point source outside the enclosure and propagated through the enclosure wall and excites an aluminium flexible panel clamped onto the enclosure. The behaviour of the transmission of sound into the cavity is investigated by computing the modal characteristics and the natural frequencies of the cavity. The simulation results are compared with previous analytical and experimental works for validation and an acceptable match between them were obtained.

Theoretical Development of Minimum Effort Active Noise Control with Feedback Inclusion Architecture

This paper presents the development of minimum effort active noise control theory for feedforward single-input single output (SISO) architecture, which includes the feedback acoustic path in the controller formulation. The theoretical range of effective minimum effort parameter with respect to level of point cancellation at the observer and the interference pattern generated around the observer for periodic noise control in free-field are investigated. It is found that for a minimum of 6 dB cancellation which corresponds to cancellation factor of 0.75 at the observer, the effort parameter must be specified as less than unity. It is also found that the cancellation pattern characterised by 20 dB, 10 dB and 6 dB zones reduces significantly in terms of size with an increase in the value of the effort term.

Wavelet network based online sequential extreme learning machine for dynamic system modeling

Wavelet network (WN) has been introduced in many applications of dynamic systems modeling with different learning algorithms. In this paper an online sequential extreme learning machine (OSELM) algorithm adopted as training procedure for wavelet network based on serial-parallel nonlinear autoregressive exogenous (NARX) model. The proposed model used as system identification for nonlinear dynamic systems. The main advantage of OSELM over conventional algorithms is the ability of updating network weights sequentially through data sample-by-sample in a single learning step. This attains good performance at extremely fast learning. The initial kernel parameters of WN played a big role to ensure fast and better learning performance. Simulation of the proposed scheme applied to nonlinear dynamic systems validates that WN-OSELM is superior in terms of identification accuracy and fast learning ability compared to NN-OSELM.

Chaotic fractal search algorithm for global optimization with application to control design

This paper presents chaos-embedded optimization algorithms named as Chaotic Fractal Search (CFS). These algorithms are improved variance to original Stochastic Fractal Search (SFS) algorithm. The influence of two chaos maps which are Chebyshev map and Gauss/Mouse map on the convergence speed and fitness accuracy of the SFS are investigated in this study. Two well-known benchmark test functions with different dimension levels and landscapes were employed in order to evaluate the performance of proposed CFS algorithms in comparison to their predecessor algorithm. Furthermore, the proposed approach is implemented in the optimal tuning of conventional PID and PD-type fuzzy logic controllers for a twin rotor system (TRS) in hovering mode. The simulation study indicates that CFS algorithm with Gauss/Mouse chaotic map in both Diffusion and First Updating process outperforms other CFS algorithms and original SFS algorithm. In addition, PD-type fuzzy logic controller shows superiority over PID controller in twin rotor system control design.

ANFIS Based Model for Bispectral Index Prediction

Prediction of depth of hypnosis is important in administering optimal anaesthesia during surgical procedure. However, the effect of anaesthetic drugs on human body is a nonlinear time variant system with large inter-patient variability. Such behaviours often caused limitation to the performance of conventional model. This paper explores the possibility of using the Adaptive Neuro-Fuzzy Inference System (ANFIS) to create a model for predicting Bispectral Index (BIS). BIS is a well-studied indicator of hypnotic level. Propofol infusion rate and past values of BIS were used as the input variables for modelling. Result shows that the ANFIS model is capable of predicting BIS very well.

Linear and Nonlinear Modeling of Adult Malaysian Population's Hand Grip Strength

Hand grip strength is a known indicator of hand function and its measurement is a useful criterion in designing post hand-surgery rehabilitation program. It is established that normal grip strength of patients is correlated with age, weight, height, gender, occupation and hand dominant. In this work, predictive linear and nonlinear models based on 412 healthy average Malaysians are built using least squares and neuro-fuzzy estimators respectively. Two quality of fits are used to evaluate the accuracy of the predictive models. It was found that the neuro-fuzzy model that maps the six inputs nonlinearly is superior to the linear model in describing the input-output relationship of the data

Fuzzy Control of Grain Drying Process

This paper presents the application of fuzzy logic controller (FLC) to a grain dryer plant. Grain dryer plant is very difficult to control due to long delay process and non-linear behaviour. The controller consists of two inputs; error between actual grain moisture content and set-point, and rate of change of error. There is one fuzzy output that is used to drive the grain flow rate. Simulation tests have been carried out using the process model developed by Liu and Bakker-Arkema [1] for a cross flow grain dryer. The overall results from the tests are good and the fuzzy logic controller is stable and robust towards input disturbance. Although the design process of fuzzy logic controller is simple; however it provides very fast response to make the grain output moisture content close to the set-point and to reject disturbance exists during the grain drying process.

Modeling of sound-structure interaction in a rectangular enclosure using finite element method

In this paper the effect of periodic noise traveling into a rectangular enclosure is simulated using finite element technique using COMSOL Multiphysics software. The acoustic wave which is generated by a point source outside an enclosure propagates through the enclosure wall and excites the flexible panel which is mounted on the enclosure. The behavior of transmission of sound into the cavity is investigated by computing the modal characteristics of the cavity. Base on the model proposed, simulation part is conducted to examine the natural frequency response of system as well as to compute the distortion effect of the structure response and the acoustic pressure observed within the enclosure. The simulation results were compared with previous experimental and analytical works for validation and a good match between them were obtained.

Design of Self-tuning Minimum Effort Active Noise Control with Feedback Inclusion Architecture

This paper presents the development of a self-tuning controller design of minimum effort active noise control (ANC) for feedforward single-input single-output (SISO) architecture which includes the feedback acoustic path in the controller formulation. The controller design law is derived for suitable self-tuning implementation and the self-tuning controller is evaluated in a realistically constructed ANC simulation environment. The self-tuning controller design involves a two-stage identification process where the controller is replaced by a switch. This switch is closed and opened in sequence generating two transfer functions which are then used in constructing the controller specified by a minimum effort control law. The implementation requires an estimate of the secondary path transfer function which can be identified either online or offline. The controller design and implementation are evaluated in terms of the level of cancellation at the observer through simulation studies for various values of modified effort weighting parameter in the range 0 ≤ γ ≤ 1. It was found that the optimal controller designed using this technique which is constrained only by the accuracy of the two models identified using recursive least squares algorithm, yields good cancellation level.