Abstract: Fuzzy controllers are potential candidates for the
control of nonlinear, time variant and also complicated systems. Anti
lock brake system (ABS) which is a nonlinear system, may not be
easily controlled by classical control methods. An intelligent Fuzzy
control method is very useful for this kind of nonlinear system. A
typical antilock brake system (ABS) by sensing the wheel lockup,
releases the brakes for a short period of time, and then reapplies again
the brakes when the wheel spins up. In this paper, an intelligent fuzzy
ABS controller is designed to adjust slipping performance for variety
of roads. There are tow major sections in the proposing control
system. First section consists of tow Fuzzy-Logic Controllers (FLC)
providing optimal brake torque for both front and rear wheels.
Second section which is also a FLC provides required amount of slip
and torque references properties for different kind of roads.
Simulation results of our proposed intelligent ABS for three different
kinds of road show more reliable and better performance in compare
with two other break systems.
Abstract: The two cart inverted pendulum system is a good
bench mark for testing the performance of system dynamics and
control engineering principles. Devasia introduced this system to
study the asymptotic tracking problem for nonlinear systems. In this
paper the problem of asymptotic tracking of the two-cart with an
inverted-pendulum system to a sinusoidal reference inputs via
introducing a novel method for solving finite-horizon nonlinear
optimal control problems is presented. In this method, an iterative
method applied to state dependent Riccati equation (SDRE) to obtain
a reliable algorithm. The superiority of this technique has been shown
by simulation and comparison with the nonlinear approach.
Abstract: The minimal condition for symmetry breaking in morphogenesis of cellular population was investigated using cellular automata based on reaction-diffusion dynamics. In particular, the study looked for the possibility of the emergence of branching structures due to mechanical interactions. The model used two types of cells an external gradient. The results showed that the external gradient influenced movement of cell type-I, also revealed that clusters formed by cells type-II worked as barrier to movement of cells type-I.
Abstract: We introduce a logic-based framework for database
updating under constraints. In our framework, the constraints are
represented as an instantiated extended logic program. When performing
an update, database consistency may be violated. We provide
an approach of maintaining database consistency, and study the
conditions under which the maintenance process is deterministic. We
show that the complexity of the computations and decision problems
presented in our framework is in each case polynomial time.
Abstract: A kind of singularly perturbed boundary value problems is under consideration. In order to obtain its approximation, simple upwind difference discretization is applied. We use a moving mesh iterative algorithm based on equi-distributing of the arc-length function of the current computed piecewise linear solution. First, a maximum norm a posteriori error estimate on an arbitrary mesh is derived using a different method from the one carried out by Chen [Advances in Computational Mathematics, 24(1-4) (2006), 197-212.]. Then, basing on the properties of discrete Green-s function and the presented posteriori error estimate, we theoretically prove that the discrete solutions computed by the algorithm are first-order uniformly convergent with respect to the perturbation parameter ε.
Abstract: Detection of human emotions has many potential applications. One of application is to quantify attentiveness audience in order evaluate acoustic quality in concern hall. The subjective audio preference that based on from audience is used. To obtain fairness evaluation of acoustic quality, the research proposed system for multimodal emotion detection; one modality based on brain signals that measured using electroencephalogram (EEG) and the second modality is sequences of facial images. In the experiment, an audio signal was customized which consist of normal and disorder sounds. Furthermore, an audio signal was played in order to stimulate positive/negative emotion feedback of volunteers. EEG signal from temporal lobes, i.e. T3 and T4 was used to measured brain response and sequence of facial image was used to monitoring facial expression during volunteer hearing audio signal. On EEG signal, feature was extracted from change information in brain wave, particularly in alpha and beta wave. Feature of facial expression was extracted based on analysis of motion images. We implement an advance optical flow method to detect the most active facial muscle form normal to other emotion expression that represented in vector flow maps. The reduce problem on detection of emotion state, vector flow maps are transformed into compass mapping that represents major directions and velocities of facial movement. The results showed that the power of beta wave is increasing when disorder sound stimulation was given, however for each volunteer was giving different emotion feedback. Based on features derived from facial face images, an optical flow compass mapping was promising to use as additional information to make decision about emotion feedback.
Abstract: This paper presents a procedure for estimating VAR
using Sequential Discounting VAR (SDVAR) algorithm for online
model learning to detect fraudulent acts using the telecommunications
call detailed records (CDR). The volatility of the VAR is observed
allowing for non-linearity, outliers and change points based on the
works of [1]. This paper extends their procedure from univariate
to multivariate time series. A simulation and a case study for
detecting telecommunications fraud using CDR illustrate the use of
the algorithm in the bivariate setting.
Abstract: In this paper, we evaluate the performance of the
Hybrid-MIMO Receiver Scheme (HMRS) in Cognitive Radio
network (CR-network). We investigate the efficiency of the proposed
scheme which the energy level and user number of primary user are
varied according to the characteristic of CR-network. HMRS can
allow users to transmit either Space-Time Block Code (STBC) or
Spatial-Multiplexing (SM) streams simultaneously by using
Successive Interference Cancellation (SIC) and Maximum Likelihood
Detection (MLD). From simulation, the results indicate that the
interference level effects to the performance of HMRS. Moreover,
the exact closed-form capacity of the proposed scheme is derived and
compared with STBC scheme.
Abstract: In this paper, we propose a robust disease detection
method, called adaptive orientation code matching (Adaptive OCM),
which is developed from a robust image registration algorithm:
orientation code matching (OCM), to achieve continuous and
site-specific detection of changes in plant disease. We use two-stage
framework for realizing our research purpose; in the first stage,
adaptive OCM was employed which could not only realize the
continuous and site-specific observation of disease development, but
also shows its excellent robustness for non-rigid plant object searching
in scene illumination, translation, small rotation and occlusion changes
and then in the second stage, a machine learning method of support
vector machine (SVM) based on a feature of two dimensional (2D)
xy-color histogram is further utilized for pixel-wise disease
classification and quantification. The indoor experiment results
demonstrate the feasibility and potential of our proposed algorithm,
which could be implemented in real field situation for better
observation of plant disease development.
Abstract: In this work, simulation algorithms for contact drying
of agitated particulate materials under vacuum and at atmospheric
pressure were developed. The implementation of algorithms gives a
predictive estimation of drying rate curves and bulk bed temperature
during contact drying. The calculations are based on the penetration
model to describe the drying process, where all process parameters
such as heat and mass transfer coefficients, effective bed properties,
gas and liquid phase properties are estimated with proper
correlations. Simulation results were compared with experimental
data from the literature. In both cases, simulation results were in good
agreement with experimental data. Few deviations were identified
and the limitations of the predictive capabilities of the models are
discussed. The programs give a good insight of the drying behaviour
of the analysed powders.
Abstract: This paper focuses on the development of bond graph
dynamic model of the mechanical dynamics of an excavating mechanism
previously designed to be used with small tractors, which are
fabricated in the Engineering Workshops of Jomo Kenyatta University
of Agriculture and Technology. To develop a mechanical dynamics
model of the manipulator, forward recursive equations similar to
those applied in iterative Newton-Euler method were used to obtain
kinematic relationships between the time rates of joint variables
and the generalized cartesian velocities for the centroids of the
links. Representing the obtained kinematic relationships in bondgraphic
form, while considering the link weights and momenta as
the elements led to a detailed bond graph model of the manipulator.
The bond graph method was found to reduce significantly the number
of recursive computations performed on a 3 DOF manipulator for a
mechanical dynamic model to result, hence indicating that bond graph
method is more computationally efficient than the Newton-Euler
method in developing dynamic models of 3 DOF planar manipulators.
The model was verified by comparing the joint torque expressions
of a two link planar manipulator to those obtained using Newton-
Euler and Lagrangian methods as analyzed in robotic textbooks. The
expressions were found to agree indicating that the model captures
the aspects of rigid body dynamics of the manipulator. Based on
the model developed, actuator sizing and valve sizing methodologies
were developed and used to obtain the optimal sizes of the pistons
and spool valve ports respectively. It was found that using the pump
with the sized flow rate capacity, the engine of the tractor is able to
power the excavating mechanism in digging a sandy-loom soil.
Abstract: The study of the fouling deposition of pink guava
juice (PGJ) is relatively new research compared to milk fouling
deposit. In this work, a new experimental set-up was developed to
imitate the fouling formation in heat exchanger, namely a continuous
flow experimental set-up heat exchanger. The new experimental setup
was operated under industrial pasteurization temperature of PGJ,
which was at 93°C. While the flow rate and pasteurization period
were based on the experimental capacity, which were 0.5 and 1
liter/min for the flow rate and the pasteurization period was set for 1
hour. Characterization of the fouling deposit was determined by
using various methods. Microstructure of the deposits was carried
out using ESEM. Proximate analyses were performed to determine
the composition of moisture, fat, protein, fiber, ash and carbohydrate
content. A study on the hardness and stickiness of the fouling deposit
was done using a texture analyzer. The presence of seedstone in pink
guava juice was also analyzed using a particle analyzer. The findings
shown that seedstone from pink guava juice ranging from 168 to
200μm and carbohydrate was found to be a major composition
(47.7% of fouling deposit consists of carbohydrate). Comparison
between the hardness and stickiness of the deposits at two different
flow rates showed that fouling deposits were harder and denser at
higher flow rate. Findings from this work provide basis knowledge
for further study on fouling and cleaning of PGJ.
Abstract: This paper discusses the utilization of marine biomass as an energy resource in Japan. A marine biomass energy system in Japan was proposed consisting of seaweed cultivation (Laminaria japonica) at offshore marine farms, biogas production via methane fermentation of the seaweeds, and fuel cell power generation driven by the generated biogas. We estimated energy output, energy supply potential, and CO2 mitigation in Japan on the basis of the proposed system. As a result, annual energy production was estimated to be 1.02-109 kWh/yr at nine available sites. Total CO2 mitigation was estimated to be 1.04-106 tonnes per annum at the nine sites. However, the CO2 emission for the construction of relevant facilities is not taken into account in this paper. The estimated CO2 mitigation is equivalent to about 0.9% of the required CO2 mitigation for Japan per annum under the Kyoto Protocol framework.
Abstract: In this paper, naturally immobilized lipase, Carica
papaya lipase, catalyzed biodiesel production from fish oil was
studied. The refined fish oil, extracted from the discarded parts of
fish, was used as a starting material for biodiesel production. The
effects of molar ratio of oil: methanol, lipase dosage, initial water
activity of lipase, temperature and solvent were investigated. It was
found that Carica papaya lipase was suitable for methanolysis of fish
oil to produce methyl ester. The maximum yield of methyl ester
could reach up to 83% with the optimal reaction conditions: oil:
methanol molar ratio of 1: 4, 20% (based on oil) of lipase, initial
water activity of lipase at 0.23 and 20% (based on oil) of tert-butanol
at 40oC after 18 h of reaction time. There was negligible loss in
lipase activity even after repeated use for 30 cycles.
Abstract: Motion detection is very important in image
processing. One way of detecting motion is using optical flow.
Optical flow cannot be computed locally, since only one independent
measurement is available from the image sequence at a point, while
the flow velocity has two components. A second constraint is needed.
The method used for finding the optical flow in this project is
assuming that the apparent velocity of the brightness pattern varies
smoothly almost everywhere in the image. This technique is later
used in developing software for motion detection which has the
capability to carry out four types of motion detection. The motion
detection software presented in this project also can highlight motion
region, count motion level as well as counting object numbers. Many
objects such as vehicles and human from video streams can be
recognized by applying optical flow technique.
Abstract: According to the Auckland climate, building passive
design more focus on improving winter indoor thermal and health
conditions. Based on field study data of indoor air temperature and
relative humidity close to ceiling and floor of an insulated Auckland
townhouse with and without a whole home mechanical ventilation
system, this study is to analysis variation of indoor microclimate data
of an Auckland townhouse using or not using the mechanical
ventilation system to evaluate winter indoor thermal and health
conditions for the future house design with a mechanical ventilation
system.
Abstract: Tasks of an application program of an embedded system are managed by the scheduler of a real-time operating system
(RTOS). Most RTOSs adopt just fixed priority scheduling, which is not optimal in all cases. Some applications require earliest deadline
first (EDF) scheduling, which is an optimal scheduling algorithm.
In order to develop an efficient real-time embedded system, the
scheduling algorithm of the RTOS should be selectable. The paper presents a method to customize the scheduler using aspectoriented
programming. We define aspects to replace the fixed priority scheduling mechanism of an OSEK OS with an EDF scheduling
mechanism. By using the aspects, we can customize the scheduler
without modifying the original source code. We have applied the
aspects to an OSEK OS and get a customized operating system with
EDF scheduling. The evaluation results show that the overhead of
aspect-oriented programming is small enough.
Abstract: The two-dimensional gel electrophoresis method
(2-DE) is widely used in Proteomics to separate thousands of proteins
in a sample. By comparing the protein expression levels of proteins in
a normal sample with those in a diseased one, it is possible to identify
a meaningful set of marker proteins for the targeted disease. The major
shortcomings of this approach involve inherent noises and irregular
geometric distortions of spots observed in 2-DE images. Various
experimental conditions can be the major causes of these problems. In
the protein analysis of samples, these problems eventually lead to
incorrect conclusions. In order to minimize the influence of these
problems, this paper proposes a partition based pair extension method
that performs spot-matching on a set of gel images multiple times and
segregates more reliable mapping results which can improve the
accuracy of gel image analysis. The improved accuracy of the
proposed method is analyzed through various experiments on real
2-DE images of human liver tissues.
Abstract: The aim of this study is to examine the reading
comprehension scores of Turkish 5th grade students according to the
variables given in the student questionnaire. In this descriptive
survey study research participated 279 5th grade students, who
studied at 10 different primary schools in four provinces of Ankara in
2008-2009 academic year. Two different data collection tools were
made use of in the study: “Reading Comprehension Test" and
“Student Information Questionnaire". Independent sample t-test, oneway
Anova and two-way Anova tests were used in the analyses of
the gathered data. The results of the study indicate that the reading
comprehension scores of the students differ significantly according to
sex of the students, the number of books in their houses, the
frequency of summarizing activities on the reading text of free and
the frequency reading hours provided by their teachers; but, differ
not significantly according to educational level of their mothers and
fathers.
Abstract: Droplet size distributions in the cold spray of a fuel
are important in observed combustion behavior. Specification of
droplet size and velocity distributions in the immediate downstream
of injectors is also essential as boundary conditions for advanced
computational fluid dynamics (CFD) and two-phase spray transport
calculations. This paper describes the development of a new model to
be incorporated into maximum entropy principle (MEP) formalism
for prediction of droplet size distribution in droplet formation region.
The MEP approach can predict the most likely droplet size and
velocity distributions under a set of constraints expressing the
available information related to the distribution.
In this article, by considering the mechanisms of turbulence
generation inside the nozzle and wave growth on jet surface, it is
attempted to provide a logical framework coupling the flow inside the
nozzle to the resulting atomization process. The purpose of this paper
is to describe the formulation of this new model and to incorporate it
into the maximum entropy principle (MEP) by coupling sub-models
together using source terms of momentum and energy. Comparison
between the model prediction and experimental data for a gas turbine
swirling nozzle and an annular spray indicate good agreement
between model and experiment.