Abstract: This paper describes the application of a model
predictive controller to the problem of batch reactor temperature
control. Although a great deal of work has been done to improve
reactor throughput using batch sequence control, the control of the
actual reactor temperature remains a difficult problem for many
operators of these processes. Temperature control is important as
many chemical reactions are sensitive to temperature for formation of
desired products. This controller consist of two part (1) a nonlinear
control method GLC (Global Linearizing Control) to create a linear
model of system and (2) a Model predictive controller used to obtain
optimal input control sequence. The temperature of reactor is tuned
to track a predetermined temperature trajectory that applied to the
batch reactor. To do so two input signals, electrical powers and the
flow of coolant in the coil are used. Simulation results show that the
proposed controller has a remarkable performance for tracking
reference trajectory while at the same time it is robust against noise
imposed to system output.
Abstract: Constant upgrading of Enterprise Resource Planning
(ERP) systems is necessary, but can cause new defects. This paper
attempts to model the likelihood of defects after completed upgrades
with Weibull defect probability density function (PDF). A case study
is presented analyzing data of recorded defects obtained for one ERP
subsystem. The trends are observed for the value of the parameters
relevant to the proposed statistical Weibull distribution for a given
one year period. As a result, the ability to predict the appearance of
defects after the next upgrade is described.
Abstract: Polynomial maps offer analytical properties used to obtain better performances in the scope of chaos synchronization under noisy channels. This paper presents a new method to simplify equations of the Exact Polynomial Kalman Filter (ExPKF) given in [1]. This faster algorithm is compared to other estimators showing that performances of all considered observers vanish rapidly with the channel noise making application of chaos synchronization intractable. Simulation of ExPKF shows that saturation drawn on the emitter to keep it stable impacts badly performances for low channel noise. Then we propose a particle filter that outperforms all other Kalman structured observers in the case of noisy channels.
Abstract: In the globalized e-learning environment, students coming from different cultures and countries have different characteristics and require different support designed for their approaches to study and learning styles. This paper explores the ways in which cultural background influences students- approaches to study and learning styles. Participants in the study consisted of 131 eastern students and 54 western students from an Australian university. The students were tested using the Study Process Questionnaire (SPQ) for assessing their approaches to study and the Index of Learning Styles Questionnaire (ILS) for assessing their learning styles. The results of the study led to a set of principles being proposed to guide personalization of e-learning system design on the basis of cultural differences.
Abstract: This research aims to study value-creation process of
producing monk-s bowls, Thai traditional handicrafts, which is facing problems in adapting to the changing society. It also aims to identify
problems and obstacles to value creation. This research is based on a case study of monk-s bowl manufactures from Ban-Baat Village,
Bangkok. The conceptual framework is based on the model of value
chain to analyze the process.
The research methodology is qualitative. This research found that the value-creation process of monk-s bowls consists of eight
activities contributing to adding value to the products and increasing
profits to the producers in return. Five major problems and obstacles
are found.
The research suggests that these problems and obstacles limit the manufacturers- potential for creating more valued product and lead to business stagnation. These problems should be addressed and solved with collaboration among the government, the private sector and the
manufacturers.
Abstract: The present work is a numerical simulation of
nanofluids flow in a double pipe heat exchanger provided with
porous baffles. The hot nanofluid flows in the inner cylinder, whereas
the cold nanofluid circulates in the annular gap. The Darcy-
Brinkman-Forchheimer model is adopted to describe the flow in the
porous regions, and the governing equations with the appropriate
boundary conditions are solved by the finite volume method. The
results reveal that the addition of metallic nanoparticles enhances the
rate of heat transfer in comparison to conventional fluids but this
augmentation is accompanied by an increase in pressure drop. The
highest heat exchanger performances are obtained when
nanoparticles are added only to the cold fluid.
Abstract: In this paper, frequency offset (FO) estimation schemes
robust to the non-Gaussian noise environments are proposed for
orthogonal frequency division multiplexing (OFDM) systems. First,
a maximum-likelihood (ML) estimation scheme in non-Gaussian
noise environments is proposed, and then, the complexity of the
ML estimation scheme is reduced by employing a reduced set of
candidate values. In numerical results, it is demonstrated that the
proposed schemes provide a significant performance improvement
over the conventional estimation scheme in non-Gaussian noise
environments while maintaining the performance similar to the
estimation performance in Gaussian noise environments.
Abstract: Methods of contemporary mathematical physics such
as chaos theory are useful for analyzing and understanding the
behavior of complex biological and physiological systems. The three
dimensional model of HIV/AIDS is the basis of active research since
it provides a complete characterization of disease dynamics and the
interaction of HIV-1 with the immune system. In this work, the
behavior of the HIV system is analyzed using the three dimensional
HIV model and a chaotic measure known as the Hurst exponent.
Results demonstrate that Hurst exponents of CD4, CD8 cells and
viral load vary nonlinearly with respect to variations in system
parameters. Further, it was observed that the three dimensional HIV
model can accommodate both persistent (H>0.5) and anti-persistent
(H
Abstract: Recently, Jia et al. proposed a remote user authentication scheme using bilinear pairings and an Elliptic Curve Cryptosystem (ECC). However, the scheme is vulnerable to privileged insider attack at their proposed registration phase and to forgery attack at their proposed authentication phase. In addition, the scheme can be vulnerable to server spoofing attack because it does not provide mutual authentication between the user and the remote server. Therefore, this paper points out that the Jia et al. scheme is vulnerable to the above three attacks.
Abstract: The aim of this study was to investigate the influence
of reaction temperature and wheat straw moisture content on the
pyrolysis product yields, in the temperature range of 475-575 °C.
Samples of straw with moisture contents from 1.5 wt % to 15.0 wt %
were fed to a bench scale Pyrolysis Centrifuge Reactor (PCR). The
experimental results show that the changes in straw moisture content
have no significant effect on the distribution of pyrolysis product
yields. The maximum bio-oil yields approximately 60 (wt %, on dry
ash free feedstock basis) was observed around 525 °C - 550 °C for all
straw moisture levels. The water content in the wet straw bio-oil was
the highest. The heating value of bio-oil and solid char were
measured and the percentages of its energy distribution were
calculated. The energy distributions of bio-oil, char and gas were 56-
69 % 24-33 %, and 2-19 %, respectively.
Abstract: One of the most important problems in production planning of flexible manufacturing system (FMS) is machine tool selection and operation allocation problem that directly influences the production costs and times .In this paper minimizing machining cost, set-up cost and material handling cost as a multi-objective problem in flexible manufacturing systems environment are considered. We present a 0-1 integer linear programming model for the multiobjective machine tool selection and operation allocation problem and due to the large scale nature of the problem, solving the problem to obtain optimal solution in a reasonable time is infeasible, Paretoant colony optimization (P-ACO) approach for solving the multiobjective problem in reasonable time is developed. Experimental results indicate effectiveness of the proposed algorithm for solving the problem.
Abstract: This paper presents the investigation results of UV
measurement at different level of altitudes and the development of a
new portable instrument for measuring UV. The rapid growth of
industrial sectors in developing countries including Malaysia, brings
not only income to the nation, but also causes pollution in various
forms. Air pollution is one of the significant contributors to global
warming by depleting the Ozone layer, which would reduce the
filtration of UV rays. Long duration of exposure to high to UV rays
has many devastating health effects to mankind directly or indirectly
through destruction of the natural resources. This study aimed to
show correlation between UV and altitudes which indirectly can help
predict Ozone depletion. An instrument had been designed to
measure and monitors the level of UV. The instrument comprises of
two main blocks namely data logger and Graphic User Interface
(GUI). Three sensors were used in the data logger to detect changes
in the temperature, humidity and ultraviolet. The system has
undergone experimental measurement to capture data at two different
conditions; industrial area and high attitude area. The performance of
the instrument showed consistency in the data captured and the
results of the experiment drew a significantly high reading of UV at
high altitudes.
Abstract: Field experiments were carried out at Owo, southwest Nigeria to evaluate the effect of different tillage practices (zero tillage with mulch (ZTM), row tillage (RT) and conventional tillage (CT), and with or without oil palm bunch ash plus poultry manure (OBA+PM) on soil chemical properties, growth and yield of ginger. The experiment was laid out in a randomized complete plot design with three replications. Soil chemical properties, growth and fresh rhizome yield reduced with frequency/intensity of tillage imposed while application of OBA+PM increased them. Among the tillage practices, the highest fresh rhizome yield (15.0t ha-1) was produced by ZTM which was significantly different from other tillage practices. Among the tillage – OBA+PM combinations, the most satisfactorily yield (20.1t ha-1) was produced by ZTM+OBA+PM while the lowest yield (15.7t ha-1) was in CT+OBA+PM.
Abstract: The paper evaluates several hundred one-day-ahead
VaR forecasting models in the time period between the years 2004
and 2009 on data from six world stock indices - DJI, GSPC, IXIC,
FTSE, GDAXI and N225. The models model mean using the ARMA
processes with up to two lags and variance with one of GARCH,
EGARCH or TARCH processes with up to two lags. The models are
estimated on the data from the in-sample period and their forecasting
accuracy is evaluated on the out-of-sample data, which are more
volatile. The main aim of the paper is to test whether a model
estimated on data with lower volatility can be used in periods with
higher volatility. The evaluation is based on the conditional coverage
test and is performed on each stock index separately. The primary
result of the paper is that the volatility is best modelled using a
GARCH process and that an ARMA process pattern cannot be found
in analyzed time series.
Abstract: In this study, a mathematical model was proposed and
the accuracy of this model was assessed to predict the growth of
Pseudomonas aeruginosa and rhamnolipid production under nitrogen
limiting (sodium nitrate) fed-batch fermentation. All of the
parameters used in this model were achieved individually without
using any data from the literature.
The overall growth kinetic of the strain was evaluated using a
dual-parallel substrate Monod equation which was described by
several batch experimental data. Fed-batch data under different
glycerol (as the sole carbon source, C/N=10) concentrations and feed
flow rates were used to describe the proposed fed-batch model and
other parameters. In order to verify the accuracy of the proposed
model several verification experiments were performed in a vast
range of initial glycerol concentrations. While the results showed an
acceptable prediction for rhamnolipid production (less than 10%
error), in case of biomass prediction the errors were less than 23%. It
was also found that the rhamnolipid production by P. aeruginosa was
more sensitive at low glycerol concentrations.
Based on the findings of this work, it was concluded that the
proposed model could effectively be employed for rhamnolipid
production by this strain under fed-batch fermentation on up to 80 g l-
1 glycerol.
Abstract: In the present work, the performance of the particle
swarm optimization and the genetic algorithm compared as a typical
geometry design problem. The design maximizes the heat transfer
rate from a given fin volume. The analysis presumes that a linear
temperature distribution along the fin. The fin profile generated using
the B-spline curves and controlled by the change of control point
coordinates. An inverse method applied to find the appropriate fin
geometry yield the linear temperature distribution along the fin
corresponds to optimum design. The numbers of the populations, the
count of iterations and time to convergence measure efficiency.
Results show that the particle swarm optimization is most efficient
for geometry optimization.
Abstract: Association rules are an important problem in data
mining. Massively increasing volume of data in real life databases
has motivated researchers to design novel and incremental algorithms
for association rules mining. In this paper, we propose an incremental
association rules mining algorithm that integrates shocking
interestingness criterion during the process of building the model. A
new interesting measure called shocking measure is introduced. One
of the main features of the proposed approach is to capture the user
background knowledge, which is monotonically augmented. The
incremental model that reflects the changing data and the user beliefs
is attractive in order to make the over all KDD process more
effective and efficient. We implemented the proposed approach and
experiment it with some public datasets and found the results quite
promising.
Abstract: A flow line computational technique based on the D8
method using Mathematica was developed. The technique was
applied to Ron Phibun area, Nakhon Si Thammarat Province. This
area is highly contaminated with arsenic 3 and 5. It was found that
the technique using Mathematica can produce similar results to those
obtained from GRASS v 5.0.2.
Abstract: Acoustic function plays an important role in
aerodynamic mechanical engineering. It can classify the kind of
air-vehicle such as subsonic or supersonic. Acoustic velocity
relates with velocity and Mach number. Mach number relates
again acoustic stability or instability condition. Mach number
plays an important role in growth or decay in energy system.
Acoustic is a function of temperature and temperature is directly
proportional to pressure. If we control the pressure, we can control
acoustic function. To get pressure stability condition, we apply
Navier-Stokes equations.
Abstract: An automated wood recognition system is designed to
classify tropical wood species.The wood features are extracted based
on two feature extractors: Basic Grey Level Aura Matrix (BGLAM)
technique and statistical properties of pores distribution (SPPD)
technique. Due to the nonlinearity of the tropical wood species
separation boundaries, a pre classification stage is proposed which
consists ofKmeans clusteringand kernel discriminant analysis (KDA).
Finally, Linear Discriminant Analysis (LDA) classifier and KNearest
Neighbour (KNN) are implemented for comparison purposes.
The study involves comparison of the system with and without pre
classification using KNN classifier and LDA classifier.The results
show that the inclusion of the pre classification stage has improved
the accuracy of both the LDA and KNN classifiers by more than
12%.