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This dissertation presents a computer learning assistant ILMEV (Interactive Learning -Mathematica Enhanced Vector calculus), that helps students understand the theory and applications of integration in vector calculus. Many students in engineering, the physical sciences and mathematics are required to learn vector calculus and find the subject challenging. Learning assistants in such advanced applied mathematics are rare and present many challenges. First, the presentation of this material in textbooks is not suitable for an automated assistant and thus, had to be substantially reorganized. Additionally, no computer algebra system has algorithms powerful enough to automatically solve all but the most elementary problems of this type that appear in textbooks. To overcome this, we implemented a geometric modeler and a simplified version of the cylindrical algebraic decomposition (CAD) algorithm so that ILMEV can now compute closed form solutions to many two dimensional textbook examples as well as examples far more complex. ILMEV succeeds because it contains algorithms for reducing the integrals appearing in vector calculus to sums of iterated integrals and all computer algebra systems have powerful algorithms for computing iterated integrals in closed form. Vector calculus is complicated, requiring the correct application of many formulas which, in turn, requires extensive calculations involving calculus and algebra. It is vital that students acquire good intuition about complex geometric objects. Consequently, the design of an assistant must be based on the best pedagogical principles (interactivity, visualization and experimentation) to assist in the teaching and learning. One important aspect of ILMEV is that it proceeds in simple logical steps and explains what it is doing. All of this would be for naught if ILMEV does not have an easy to use interface that enables student access to the power of a computer algebra system.

The importance of providing multicast services to mobile users is accelerated by the fact that the mobile Internet users expect to have access to the services that are available in wired networks. One of the most popular services is the multimedia application, in which multicast is the most suitable choice. However, integrating multicasting with mobility creates many challenges, because the network must deal not only with dynamic group membership, but also with the dynamic locations of mobile hosts. Mobile IPv6/v4 (MIP) proposes two solutions to handle the node movement in multicast transmission. The first approach is Bidirectional Tunneling (BT) where the Mobile Node (MN) receives/sends the multicast datagram through its Home Agent (HA). The second approach is Remote Subscription (RS) where the MN re-subscribes to the multicast group through a local multicast router at the foreign network. BT approach hides the mobility; however it introduces a serious triangular routing problem. RS approach provides an optimal routing; however it suffers from serious frequent multicast tree reconstruction. The objective of this thesis is to provide seamless mobile multicast support by developing a set of robust protocols that facilitate and improve senders/receivers mobility, and result in low signaling cost during an ongoing multicast session. This is achieved by hiding the multicast node local mobility and avoiding the single point of failure. The proposed set of protocols, Robust Multicast using Hierarchical Mobile IPv6 (RM-HM), integrates the advantages of BT and RS approaches and benefits from the infrastructure of Hierarchical Mobile IP (HMIP) to hide the MN mobility. Evaluation of the proposed protocols is based on analytical approach and via simulating Internet-like topologies. The simulation is carried out using the Network Simulator (NS-2) and the Network Manipulator (NEM). Metrics considered are: the gain in the delivery length and delay, and the impact of the multicast group size. The obtained results are compared to the standard approaches proposed by MIP. The results shows that the proposed protocols experience low signaling cost, perform less tree reconstructions, less multicast latency and better routing efficiency, and provide higher availability.

Due to several biological characteristics, bacterial phytate-degrading enzymes have considerable potential in commercial and environmental applications. Until now, there is no single phytase that is able to meet the diverse needs for all commercial and environmental applications. Phytase enzyme preparations have a wide range of applications in animal and human nutrition as well as bio fertilizer. Bacteria strains were isolated from Malaysian maize fields and roots, and screened for phytatedegrading enzyme activity. The production and purification of extra-cellular phytatedegrading enzyme from the most potential strain as phytase producer, Enterobacter sakazakiii ASUIA279 was optimized using response surface methodology (RSM) with full-factorial faced centered central composite design (FCCCD). An extracellular phytate-degrading enzyme synthesized by E. sakazakii ASUIA279 was purified to homogeneity using FPLC anion exchange chromatography and gel filtration. The arrangement of the bacterial isolates according to their ability to produce extra-cellular phytate-degrading enzymes were Enterobacter sakazakii ASUIA279 > Pantoea stewartii ASUIA271 > Bacillus cereus ASUIA260. The optimum combination of cultivation conditions for maximum phytate-degrading enzyme production were determined at incubation temperature which is 39.7 ºC, initial pH 7.1, rice bran percentage at 13.6 %, 320 rpm of agitation and 0 vvm of aeration. The optimum combinations of experimental conditions in ion exchange chromatography were at pH 5.1 and 47 mM of sodium acetate buffer. Its molecular mass was estimated to be 43 kDa by SDS-PAGE. The Machaelis constant (KM) and turnover number (kcat ) for sodium phytate at pH 5.0 and 50 °C were calculated from the Lineweaver-Burk plot to 760 µM and 4.14 s-1, respectively. Optimal activity was determined at pH 4.5 and 50 ± 5 °C. The enzyme was strongly inhibited by Fe3+, Cu2+, Zn2+, molybdate, vanadate, fluoride and phosphate (1 mM). In this study, an extracellular phytate-degrading enzyme with promising properties as an animal feed additives or soil nutrient enhancement produced by E. sakazakii ASUIA279, a newly isolated bacteria strain was obtained. The phytate-degrading enzyme synthesis by these bacteria was triggered by the high content of organic phytate in the rice bran. Rice bran could be utilized and developed as a media for the production of this enzyme.

Comprehensive comparison on quarter-car, half-car and full-car models were conducted to analyze the effect of using semiactive control policies, namely skyhook, groundhook and hybrid controls, in improving ride quality of passenger vehicle. Sprung mass acceleration, suspension deflection and tire deflection responses were analyzed for measurements of ride quality, rattle-space and road holding. Three different analyses were conducted on each model; frequency-domain transfer function analysis, time-domain transient state and steady state analysis. Results shows that hybrid control policy gives significant improvements in most responses while at the same time it does not compromise road holding ability of vehicle. Further quantitative comparison of responses on all three models shows that quarter-car model is unable to accurately represent responses in full-car model. Half-car model gives reasonable representation of full-car model in some states. RMS analysis conducted on a H-car 2-DOF system shows good agreement to the previous work on Q-car 2-DOF. This book should benefit researchers working in the area of semiactive control of vehicle suspension system

Internet growth in recent years has encouraged many new applications to be provided for the user such as video conferencing and video telephony. Most of these new applications require data involving images characterized by a large number of bits. Therefore, it is a difficult task to implement these types of applications since the data needs to be transferred from one place to another over the network. Moreover, these applications are intended to be real time applications implying that they are very sensitive to delay and jitter which add to the challenges of providing such applications. Consequently, two strategies are needed in order to meet the challenges of transferring and storing very high volume of data for the application while maintaining strict requirement for delay and jitter. The first strategy involves qualitative and quantitative optimization of the application’s data. The qualitative optimization ensures that the data of the application meets at least a minimum quality requirement (e.g. image resolution). Quantitative optimization is accomplished by using compression techniques to reduce the number of bits that are required to be transmitted over the network. The second strategy involves optimizing the utilization and performance of the network. This research, which consists of two phases, examines an optimized approach for transferring and storing images. Phase one deals with the processing and compressing of the images. Processing the images is done by applying an adaptive filter in order to enhance the visual quality while compression is used to reduce the amount of data needed to be stored or transmitted. The study developed a Multilayer Feed Forward Artificial Neural Network (MFFANN) for image compression. Based on Gradient Descent, Conjugate Gradient, Quasi-Newton techniques, three different error back propagation algorithms were developed for use in training the MFFANN. The essence of this study is to investigate the most efficient and effective training methods for use in image compression and its subsequent applications. The results show that the Quasi-Newton based algorithm has a better performance as compared to the other two algorithms. In Phase two, the study proposes a new admission control mechanism that aims to enable Multi Protocol Label Switching (MPLS) tunnel differentiations. It also presents a simulation based evaluation for the proposed mechanism. The results demonstrate the effectiveness of the proposal, as it is able to maintain a robust and stable end-to-end quality of service for selected flows, which leads to a better performance in terms of throughput, delay and jitter. The implementation of the optimization approach presented in this research could be highly beneficial in providing online real time services such as medical services, where consultation or even remote medical operations could take place using the Internet.

The study for the production of citric acid from oil palm empty fruit bunches (EFB) by solid state bioconversion using locally isolated Aspergillus niger was conducted by several approaches. The main objective of the study was to produce citric acid from EFB by solid state bioconversion using locally isolated Aspergillus niger. A total of 29 fungal strains were isolated from two different sources: orange and lemon, among which 21 strains belong to the genera of Aspergillus, five strains to Penicillium and three strains to Rhyzopus. Three strains, i.e. A. niger IBO-103MNB, A. niger IBO- 109MNB and A. niger IBO-114MNB were found to be potential in terms of citric acid production, growth, consumption of sugar and evolution of pH during the bioconversion through the screening test among the 26 strains of A. niger including five strains from laboratory stock. None of the mixed cultures of these three potential strains were found to be compatible in terms of mutual intermingling growth as well as production of citric acid, growth, consumption of sugar, lignocellulolytic enzymes secretion and evolution of pH. The strain A. niger IBO-103MNB was found to be potential for citric acid production by comparing the results of the single culture and their mixed cultures. Particle size of EFB and its distribution showed the important role on improvement of citric acid production. Well-graded particle size distribution of 0.5 mm down graded particle was found to be suitable for the improvement of citric acid production. On the other hand, non-treated EFB was found to be better than the sample treated by H2SO4, NaOH and boiling in water. The optimization results showed that the media constituents and the inoculum dose highly influenced the production of citric acid from EFB. The sucrose content of 6.4% (w/w), mineral content of 9% (v/w) (Zn 8.1, Cu 9, Mn 36 and Mg 450 mg/kg-EFB), methanol concentration of 2% (v/w) and inoculum concentration of 15.5% (v/w) were found to be the optimum conditions for the maximum production of 337.94 g/kg-EFB citric acid. The optimum process conditions: moisture content of 71.70% (v/w), initial pH of 6.0 and incubation temperature of 32.5oC significantly affected the bioconversion process for citric acid production of 370.6 g/kg-EFB. The highest production of citric acid of 417.95±5.33 g/kg-EFB with the productivity of 59.7±0.8 g/kg-EFB-day was obtained after seven days of bioconversion with optimum media constituents and process conditions in 250 ml Erlenmeyer flask. The highest yield of citric acid production based on sugar consumption (YP/S) was 0.774 g/g. It was observed that about 61.6% of cellulose and 33% of hemicellulose were degraded into total sugar of 394.27±4.2 g/kg-EFB which is 39.4% of the total EFB. The highest citric acid of 419.45±6.4 g/kg-EFB can be extracted from the fermented substrate with the optimum agitation of 160 rpm, solvent ratio of 9.6 and agitation duration of 56 minutes. The optimum media and process conditions obtained from flask experiment were employed to optimize the operating conditions of semi-pilot scale production in a horizontal drum bioreactor. The highest production of citric acid of 327.67±3.7 g/kg- EFB was obtained in horizontal drum bioreactor with the continuous supply of saturated air of 8.4 L/min (2.8 L/kg/min) and the agitation of 90 rotation/day (3 times per day with 3 rpm for 10 minutes. The findings of the present study might contribute to the economic development by encouraging for proper management of oil palm industry biomass as well as other lignocellulosic residues.

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The serious impact of the trailing vortices from large aircraft is well known. Many examples exist of the damage caused to following aircraft caught up in the swirling wake shed from an upstream aircraft. Motivation behind the present investigation is the alleviation of the rolling moment induced on the following aircraft by means of a differential spoiler setting DSS's. An experimental investigation on a wing tip vortex generated by generic aircraft model, Subsonic Wall Interference Model (SWIM) in plain and flapped wing configurations was conducted in a low speed wind tunnel at Korean Aerospace Research Institute (KARI). Particle image velocimetry was used to characterize wing tip vortex structures as well as to distinguish and quantify vortex meandering and further remove its effects. In subsequent experiments investigation on wake vortices has been carried out in the international Islamic University Malaysia (IIUM) low speed wind tunnel for the evaluation of differential spoiler settings (DSS) capabilities in modifying the span-wise wing load and further reduces the wake vortex hazard. Advanced PIV technique was used to measure the wake velocities at four cross-section planes down-stream of the aircraft half model in the near and extended near wake field. Model was investigated at high lift configuration as well as at four DSS configurations believed to modify the span-wise wing loading (two inboard and two outboard loading cases). Results reveal a noticeable inboard shift of wing loading along with the direct interaction of the spoiler's wake and flap tip vortex for the inboard loading cases. Implementation of DSS results in a substantial redistribution of the flap tip vortex circulation with a diameter of the merged vortex increased by a factor of up to 2.72 times, relative to the undisturbed flap tip vortex. Inspection of the cross-stream distribution of axial vorticity shows up to 2.33 times reduction in the peak vorticity value. A 44% decrease of the maximum cross-flow velocity was recorded for the case of deployed spoilers relative to undisturbed flap tip vortex maximum cross-flow velocity. The wing tip vortex experiences the effect of wing load modification but doesn't show appreciable difference, both in terms of cross-flow velocity and local circulation distribution. Evaluations of the outboard loading results indicate a limited diffusion experienced by the vortex due to the increased level of turbulence. Influence of DSS's on the wake vortex structure emphasizes that separation distance (spoiler wake/wing-flap tips vortices) plays an important role in the favorable interaction expected. Finally assessment of the DSS's capabilities as a wake vortex attenuation device reveals, while position of the maximum induced rolling moments in the flap tip area is little influenced by the DSS's, the maximum induced rolling moment coefficient was reduced to a nearly one third relative to the undisturbed flap tip vortex value.

Duststorms are significant meteorological phenomena which occur in arid and semi arid areas, especially in African Sahara and Middle East deserts. However, only a limited amount of research was carried out and the available data is very scarce. A mathematical model has been developed using Mie solution of Maxwell`s equations for the scattering of electromagnetic waves. The scattering centers are assumed to be spherically shaped dielectric particles. In the proposed model the term visibility denotes the degree of the duststorm density instead of the total number of dust particles per unit volume. The proposed model shows that the microwave signal attenuation depends on; visibility, frequency, radius of dust particles and dielectric constant. The predicted attenuation by the proposed model is compared with the values measured in Saudi Arabia and Sudan. The predicted attenuation using proposed model varies 7% from the measurement done in Saudi Arabia while the differences are more than 50% by using existing models. The proposed model showed 17% variation with the measurement done in Sudan, while the prediction by existing models are more than 60%. The visibilities are less than 1 km in both cases. It shows very close agreement, than current models. Fade margins were investigated, based on long term data collected during duststorms in arid and semi arid areas of Sudan and Saudi Arabia. It is found that 2.5 dB/km and 4 dB/km margins for dust attenuation are required to achieve 99.99% reliability for microwave links operating at Ku and Kabands respectively. At frequencies above 10 GHz, it is recommended that duststorms attenuation needs to be considered in radio planning and link budget analysis. A regional propagation map should be developed to consider duststorms characteristics. The proposed model will be useful method to predict the attenuation in microwave signal due to duststorm.

Parametric models, in form of rational system transfer function, have been successfully applied to solve various problems in different fields of human endeavor. In particular, a lot of research work has been carried out on both the autoregressive (AR) and autoregressive moving average (ARMA) models as they have been successfully used in many areas of applications such as biomedical signals analysis, system identification, geophysical signal processing, speech analysis just to mention a few. ARMA model, by its structure gives a good parsimonious representation of signals, however it is difficult to estimate its parameters. On the other hand, estimation of AR parameters is relatively easier to accomplish but suffers from spectral line splitting, poor resolution and inaccurate frequency estimates, especially for noisy short data length. In this thesis, artificial neural network (ANN) and genetic algorithm (GA) have been proposed for estimating AR and ARMA model parameters. The motivation for this work lies in the ability of ANN to learn complex mappings between input and output signals which is very difficult to encompass in the conventional model parameters estimation techniques. Development of the ANN-based parametric models has been divided into two, namely real-valued neural network (RVNN) and complexvalued neural network (CVNN) and is applicable to real-valued data and complexvalued data respectively. In both cases, model parameters determination has been carried out by a process of learning from input and output data presented to the neural network. A new model order determination technique has also been investigated in this thesis. GA has been utilized in optimizing the model coefficients obtained from the trained network and in the determination of the optimal network structure and model order. The proposed techniques produce improved performance over the existing techniques especially in accurate estimation of the model coefficients at low signal to noise ratio (SNR). In addition, the newly introduced ANN-based AR model determination techniques do not suffer from poor frequency resolution at low SNR and spectral line splitting associated with some of the existing AR model parameters determination techniques. Furthermore, the proposed hybrid RVNN-based ARMA model has been successfully used to resolve closely spaced frequencies at low SNR. It is well known that magnetic resonance images (MRI) reconstruction using inverse discrete Fourier transform (IDFT) often leads to poor resolution, introduction of artifacts and Gibb`s phenomena in the reconstructed images. Though CVNN has been used to alleviate some of these shortcomings, the reconstructed images still contain some isolated spikes. In this thesis, the newly proposed CVNN based parametric models have been applied to MRI for data extrapolation and reconstruction so as to recover the truncated high frequency signals and remove isolated spikes in the reconstructed images. The results obtained when the proposed models are applied to MRI images show improved performance as almost 95% of the truncated high frequency signals were recovered. This is a significant achievement as lower values have been reported in the literature. Furthermore, this thesis considers the use of ANN-based AR modeling technique for constructing a plane to separate members of two sets for two types of applications namely PIMA diabetes and liver disorder classification problem. Results obtained from the application of the proposed algorithm on PIMA diabetes dataset give an accuracy of 83.16% as compared to 82.60% in the previous work. Similarly, in the case of liver disorder diagnosis, accuracy of 74.65% has also been obtained in this work. Finally, CVNN-based CAR model and RVNN-based AR models have been applied to complex boundary and centroidal signatures for shape classification and mould infested images analysis. Hybrid techniques involving Fourier descriptors and RVNN-based ARMA model or CVNN-based CARMA model for dynamic mould growth analysis and prediction have also been discussed in this thesis. Application of structural similarity measures on the reconstructed mould infested image using the proposed models is found to be more computationally efficient as relatively lower number of model coefficients have been used in the analysis, characterization and reconstruction of the original spatial domain boundary pixels.

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Empty fruit bunch (EFB) is one of the most abundant residues of the palm oil mill industry. Most of it left unused and being disposed to the landfill. Discharging the huge volume of empty fruit bunch (EFB) in a sanitary landfill will not only occupy a great deal of land, but also conveys an inherent potential for pollution of indigenous water resources. Moreover, palm oil processing requires large quantities of water results in palm oil mill effluent, which contains high concentration of phenolic compounds. Thus, it must be managed with extreme care to avoid adverse environmental or human health impacts. The aim of this study was to investigate the feasibility and the potential of converting palm oil industrial residue namely empty fruit bunch (EFB) into activated carbon. Powdered activated carbon samples were produced from oil palm empty fruit bunches (EFB) by varying the operating parameters of temperatures, CO2 gas flow rates and activation times using 2-level full factorial experimental design. The prepared EFB samples were carbonized for 30 minutes using nitrogen gas, followed by activation with CO2 gas. The optimum preparation conditions for PAC samples produced were investigated through adsorption tests on aqueous solution of phenol. Characterizations of the best quality AC sample prepared and the optimum conditions for adsorption of phenol were determined. Freundlich and Langmuir adsorption isotherms as well as pseudo first order and second order adsorption kinetics models on prepared AC were studied. Finally evaluation of the adsorption efficiency of the EFB based-AC was investigated in palm oil mill final effluent (POMFE) using a bench scale model. The experimental results had shown that the activated carbon prepared at activation temperature of 800ºC with CO2 gas flow rate of 0.1 L/min and activation time of 15 minutes represent the best absorbent of phenol. Characterization of the EFB based-AC showed good quality adsorbent with highly active sites and well-developed pores with BET surface area of 375m2 /g. However, the optimum conditions for adsorption of phenol were found to be PAC dose of 75 g/L, agitation speed of 150 rpm, contact time of 15 min and pH equal to 4. Freundlich and Langmuir as well as pseudo-second order kinetic models fitted the adsorption process of phenol by prepared AC. The maximum adsorption capacity of phenol (qm) was 17.36 mg/g. EFB based-AC in the bench scale model operation had shown good removals of 40% colour, 68% phenol, 61% COD, 42% BOD and 42% ammonical nitrogen at initial five minutes contact time. EFB based-AC was found comparable to the commercial grade powdered activated carbon; it is efficient adsorbent for the removal of contaminants from palm oil mill final effluent (POMFE). Thus, EFB based-AC would be promising in two ways: the industrial oil palm solid residue would be utilized for the production of activated carbon for the treatment of wastewaters including palm oil mill final effluent.

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In this thesis, the development of a robust and accurate numerical flow solver for the two- and three-dimensional compressible flow is of major interest. The underlying numerical scheme that is used to construct this so-called solver for the compressible flow is the gas-kinetic BGK (Bhatnagaar-Gross-Krook), which is based on the collisional Boltzmann model. In this study, the algorithm for the gas-kinetic BGK flow solver is firstly developed to simulate two-dimensional compressible flow which includes the inviscid, laminar and turbulent realms of the flow. Subsequently, the developed algorithm is extended to three-dimensional compressible inviscid flow. All of the numerical treatments that are applied to solve the model equations of the flows are implemented via the finite difference approach. In such approach, the convection flux terms are discretized by a semi-discrete finite difference method, where the resulting inviscid flux functions are approximated by the BGK scheme. As for the diffusion flux terms, they are discretized by a second-order central difference scheme. A two-equation turbulence model of a combined k-ε / k-ω SST (Shear-Stress-Transport) model is used to provide the required Reynolds stresses to resolve the turbulent flow. To achieve higher-order spatial accuracy, the cell interface primitive flow variables are reconstructed by the use of MUSCL (Monotone Upstream-Centered Schemes for Conservation Laws) interpolation method coupled with a minmod limiter. For advancing the solutions to another time level, an explicit-type time integration method known as the modified fourth-order Runge-Kutta is employed in the flow solver to compute steady-state solution. In order to validate the solver and at the same time investigate its computational characteristics, several flow problems belonging to the two- and three-dimensional compressible flows are specifically chosen to be numerically analyzed. Developed solver for the two-dimensional compressible inviscid flow is tested with three typical flow problems, namely, supersonic channel flow, supersonic wedge cascade, and circular arc bump. In addition, four hypersonic test cases are also solved for the inviscid flow to test numerical shock instabilities which comprise the double Mach reflection, blunt body, axisymmetric blunt body and flow passing a 15o ramp problems. As for the two-dimensional compressible laminar flow, the following four test cases are used: 7.5o compression corner, laminar flat plate, hypersonic flow past a 24o compression ramp and hypersonic flow around a blunt body. Likewise, for the two-dimensional compressible turbulent flow, the four test cases chosen are the transitional flat plate, turbulent flat plate, RAE2822 airfoil, and Sajben diffuser. When extended to three-dimensions, the solver is used to predict four typical flow problems; namely, 10o cone at Mach 2.35, normal shock at Mach 1.3, supersonic wedge flow, and channel with a circular arc bump. For all these test cases, the numerical results are compared with available analytical, experimental and published numerical results from literature. These test cases show that the developed solver is robust, accurate and better than the central difference with TVD (Total Variation Diminishing), Steger-Warming FVS (Flux Vector Splitting) and Roe’s FDS (Flux Difference Splitting) schemes, especially at high speed flow computations where the BGK scheme does not experience any shock instability as supported by the results published in this thesis.

Titanium alloys are generally regarded as difficult-to-cut materials and plentiful research works have been conducted on their machinability in the past few decades with several diverse objectives, such as improvement on tool life, surface finish and surface integrity, investigation on chip and tool wear morphology, cutting force and vibration/chatter as well as reducing cost of machining. This study introduces induction preheating as one of the new variable parameters to improve the machinability of titanium Ti-6Al-4V alloy. In the current work the influence of heating parameter i.e. preheating temperature, and the cutting variable, i.e. cutting speed, feed and axial depth of cut were investigated during end milling operation on a vertical machining center (VMC). The inserts used were uncoated tungsten-cobalt (WC-Co) carbide and polycrystalline diamond (PCD) attached to a 20 mm diameter end mill tool. The study comprehensively investigated the effect of preheating temperature on machinability parameters i.e. tool life, surface finish and cutting force. The effect of preheating on vibration/chatter, surface integrity, chip-tool contact length and chip serration morphology were also investigated. Central composite design (CCD) of response surface methodology (RSM) coupled with Design-Expert 6.0.8 software was used to develop empirical models of tool life, cutting force and surface roughness both for room temperature and preheated machining. The software was further used to maximize the tool life and concurrently minimize the surface roughness by optimising the cutting parameters and preheating temperature. As a result, in preheated machining, the performance of uncoated WC-Co was tremendously improved (almost three times compared to room temperature machining), even the values of tool life are much higher than those cutting with PCD under room temperature machining. Preheated machining substantially contributes to the reductions of vibration/ chatter and resultant cutting force, facilitating increased tool life. Furthermore, preheated machining facilitates increased chip-tool contact length, stable chip serrations resulting in reduction of tool wear rate.

In the automotive industry some components and subassemblies which were initially made of steel are now being replaced with alloys and composites which have a higher strength to weight ratio. Therefore, today's vehicles are lighter, stronger and thus have small fuel consumption. However, mounting a more powerful engine to a lighter vehicle could cause vibration induced by the dynamics of the engine and thus affecting the comfort of the passenger. One way to overcome this predicament is to modify the mounting of the engine by introducing an active engine mounting (AEM) system which consists of passive rubber mount and a linear force actuator. At the correct frequency the linear force actuator would trigger a force which has a magnitude approximately equal to the engine's disturbance force but opposite in direction. With this the force transmitted to the chassis of the vehicle would then be minimized and increases passenger's comfort. In controlling the system, especially the force actuator, numerous controllers have been introduced which include but not limited to H2 controller, hybrid of feedback and feedforward, filtered X-LMS controller, optimal controller based on Haar wavelet and other classical feedback and feedforwad controllers. Determining the controller parameters could be a major and difficult task to perform since these parameters are based on the mathematical model of the engine-chassis system which also includes the mathematical model of the engine disturbance. In this thesis an intelligent controller namely the neural network controller has been introduced to reduce controller parameters identification. The system considered in this research includes two degree and multi degree of freedom systems. The dynamics of a nonlinear actuator was also included. Two types of neural network controller that has been used in this research namely the nonlinear auto regressive moving average (NARMA-L2) and the extended minimal resource allocating network (EMRAN). The performance of the neural network based controllers was then compared with classical controller such as PID for two degree of freedom system and a Linear Quadratic Regulator (LQR) controller for the multi degree of freedom system. The ability of the EMRAN to be trained online makes it advantageous for a non-model based controller. The EMRAN neural network has the ability to add and prune hidden layer neurons and for the purpose of efficiency and additional advantage was the adoption of the 'winner-takes-all' algorithm. Results show that the EMRAN controller perform much better as compared to PID and LQR controllers for the purpose of active vibration isolation based on the reduction of the force transmitted to the chassis of the vehicle.

Summary: This study is focused on developing an efficient processing technique for Moringa oleifera seeds to produce natural coagulant for use in drinking water treatment. The produced natural coagulant can be used as an alternative to aluminum sulphate and other coagulants worldwide for water treatment. The use of present coagulant materials produce high sludge volumes needs pH adjustments, which means adding more chemicals, and the cost of water treatment is increasing rapidly. A potential solution to these problems is the production of a new natural, renewable, environmentally friendly and safe coagulant/flocculants from Moringa oleifera seed to be used in drinking water treatment. This study investigates processing Moringa oleifera seeds to concentrate the bio-active constituents which have coagulation activity. Moringa oleifera seeds were processed for oil extraction using electro thermal soxhlet. Isolation and purification of bio-active constituents was done by chromatography technique. HPLC was used to determine the molecular weight of the bio-active constituents. The molecular weight of bio-active constituents was in a low range of between 1000 – 6500 Dalton. The importance of determining the molecular weight of bio-active constituents is to find the cut off size for the proposed cross flow filtration (ultrafiltration) method. The bio-activity was determined using conventional jar test procedures, using synthetic water and river water samples. The major water quality control parameters monitored during the study was the residual turbidity for the synthetic and river water with low, medium, and high initial turbidity. The results showed residual turbidity of less than 5 NTU which is recommended by World Health Organization (WHO). The turbidity removal was found to be 95.5%, 98.5%, and 99.3% for low, medium, and high turbidity river water samples, respectively. The proposed method to isolate and purify the bio-active constituents is the cross flow filtration method, which produced the natural coagulant with very simple technique (oil extraction; salt extraction; and microfiltration through 0.20 μm). The water treatment parameters of low speed, mixing time, and the dose of processed Moringa oleifera were optimized. The optimum conditions were: 40 rpm (low speed) with mixing time of 41.28 min, the dose of processed Moringa oleifera was 0.69 mg/L. The optimum conditions of regression model were verified using synthetic and river water with low turbidity. The regression model was highly significant with p-value < 0.01 for all model terms. The turbidity removal was up to 95.1% using low initial turbidity river water without any additives. The initial river water turbidity of 32.4 NTU was reduced to residual turbidity of 1.6 NTU by using 0.75 mg/L of processed Moringa oleifera with low mixing speed of 40 rpm for 41 minutes. The microfiltration method is considered to be a practical method which needs no chemicals added. The natural coagulant produced was used with low dosages to get high turbidity removal which considered to be a breakthrough in this study and recommended to be scaled up for industry level. This product is commercially valuable at the same time it is minimizing the cost of water treatment. The production of this alternative coagulant locally can contribute to the economic development of Malaysia. The by-products (cooking oil, activated carbon, animals feed, and fertilizer) can be of an additional advantage. It is concluded that this is a zero waste industry.