Abstract: In the recent past, there has been an increasing interest
in applying evolutionary methods to Knowledge Discovery in
Databases (KDD) and a number of successful applications of Genetic
Algorithms (GA) and Genetic Programming (GP) to KDD have been
demonstrated. The most predominant representation of the
discovered knowledge is the standard Production Rules (PRs) in the
form If P Then D. The PRs, however, are unable to handle
exceptions and do not exhibit variable precision. The Censored
Production Rules (CPRs), an extension of PRs, were proposed by
Michalski & Winston that exhibit variable precision and supports an
efficient mechanism for handling exceptions. A CPR is an
augmented production rule of the form:
If P Then D Unless C, where C (Censor) is an exception to the rule.
Such rules are employed in situations, in which the conditional
statement 'If P Then D' holds frequently and the assertion C holds
rarely. By using a rule of this type we are free to ignore the exception
conditions, when the resources needed to establish its presence are
tight or there is simply no information available as to whether it
holds or not. Thus, the 'If P Then D' part of the CPR expresses
important information, while the Unless C part acts only as a switch
and changes the polarity of D to ~D.
This paper presents a classification algorithm based on evolutionary
approach that discovers comprehensible rules with exceptions in the
form of CPRs.
The proposed approach has flexible chromosome encoding, where
each chromosome corresponds to a CPR. Appropriate genetic
operators are suggested and a fitness function is proposed that
incorporates the basic constraints on CPRs. Experimental results are
presented to demonstrate the performance of the proposed algorithm.
Abstract: Open Agent System platform based on High Level
Architecture is firstly proposed to support the application involving
heterogeneous agents. The basic idea is to develop different wrappers
for different agent systems, which are wrapped as federates to join a
federation. The platform is based on High Level Architecture and the
advantages for this open standard are naturally inherited, such as
system interoperability and reuse. Especially, the federal architecture
allows different federates to be heterogeneous so as to support the
integration of different agent systems. Furthermore, both implicit
communication and explicit communication between agents can be
supported. Then, as the wrapper RTI_JADE an example, the
components are discussed. Finally, the performance of RTI_JADE is
analyzed. The results show that RTI_JADE works very efficiently.
Abstract: The software industry has been considered a critical
infrastructure for any nation. Several studies have indicated that
national competitiveness increasingly depends upon Information and
Communication Technology (ICT), and software is one of the major
components of ICT, important for both large and small enterprises.
Even though there has been strong growth in the software industry in
Thailand, the industry has faced many challenges and problems that
need to be resolved. For example, the amount of pirated software has
been rising, and Thailand still has a large gap in the digital divide.
Additionally, the adoption among SMEs has been slow. This paper
investigates various issues in the software industry in Thailand, using
information acquired through analysis of secondary sources,
observation, and focus groups. The results of this study can be used
as “lessons learned" for the development of the software industry in
any developing country.
Abstract: Active vibration control is an important problem in
structures. The objective of active vibration control is to reduce the vibrations of a system by automatic modification of the system-s
structural response. In this paper, the modeling and design of a fast
output sampling feedback controller for a smart flexible beam system embedded with shear sensors and actuators for SISO system using
Timoshenko beam theory is proposed. FEM theory, Timoshenko beam theory and the state space techniques are used to model the
aluminum cantilever beam. For the SISO case, the beam is divided into 5 finite elements and the control actuator is placed at finite
element position 1, whereas the sensor is varied from position 2 to 5, i.e., from the nearby fixed end to the free end. Controllers are
designed using FOS method and the performance of the designed FOS controller is evaluated for vibration control for 4 SISO models
of the same plant. The effect of placing the sensor at different locations on the beam is observed and the performance of the
controller is evaluated for vibration control. Some of the limitations of the Euler-Bernoulli theory such as the neglection of shear and
axial displacement are being considered here, thus giving rise to an accurate beam model. Embedded shear sensors and actuators have
been considered in this paper instead of the surface mounted sensors
and actuators for vibration suppression because of lot of advantages. In controlling the vibration modes, the first three dominant modes of
vibration of the system are considered.
Abstract: Improving performance measures in the construction
processes has been a major concern for managers and decision
makers in the industry. They seek for ways to recognize the key
factors which have the largest effect on the process. Identifying such
factors can guide them to focus on the right parts of the process in
order to gain the best possible result. In the present study design of
experiment (DOE) has been applied to a computer simulation model
of brick laying process to determine significant factors while
productivity has been chosen as the response of the experiment. To
this end, four controllable factors and their interaction have been
experimented and the best factor level has been calculated for each
one. The results indicate that three factors, namely, labor of brick,
labor of mortar and inter arrival time of mortar along with interaction
of labor of brick and labor of mortar are significant.
Abstract: A pot experiment was carried out under controlled
conditions to evaluate the residual effects of different doses of
atrazine+alachlor and foramsulfuron used in corn fields on the
growth and physiology of rapeseed (Brassica napus L.). A split-plot
experiment in CRD with 4 replications was used. The main plots
consisted of herbicide type (atrazine+alachlor mixture and
foramsulfuron) and the sub-plots were different residual doses of the
herbicides (0, 1%, 5%, 10%, 20%, 40%, 50% and 100%). 7 cm
diameter pots were filled with a virgin soil and seeds of rapeseed cv.
Hayola were planted in them. The pots were kept under controlled
conditions for 8 weeks after germination. At harvest, the growth
parameters and the chlorophyll contents of the leaves were
determined. The results showed that the growth of rapeseed plants
was completely prevented at the highest residual doses of the
herbicides (50 and 100 %). The growth parameters of rapeseed plants
were affected by all doses of both types of the herbicide as compared
to the controls. The residual effects of atrazine+alachlor mixture in
reducing the growth parameters of rapeseed were more pronounced
as compared to the residual effects of foramsulfuron alone.
Abstract: Radio propagation from point-to-point is affected by
the physical channel in many ways. A signal arriving at a destination
travels through a number of different paths which are referred to as
multi-paths. Research in this area of wireless communications has
progressed well over the years with the research taking different
angles of focus. By this is meant that some researchers focus on
ways of reducing or eluding Multipath effects whilst others focus on
ways of mitigating the effects of Multipath through compensation
schemes. Baseband processing is seen as one field of signal
processing that is cardinal to the advancement of software defined
radio technology. This has led to wide research into the carrying out
certain algorithms at baseband. This paper considers compensating
for Multipath for Frequency Modulated signals. The compensation
process is carried out at Radio frequency (RF) and at Quadrature
baseband (QBB) and the results are compared. Simulations are
carried out using MatLab so as to show the benefits of working at
lower QBB frequencies than at RF.
Abstract: Heart disease (HD) is a major cause of morbidity and mortality in the modern society. Medical diagnosis is an important but complicated task that should be performed accurately and efficiently and its automation would be very useful. All doctors are unfortunately not equally skilled in every sub specialty and they are in many places a scarce resource. A system for automated medical diagnosis would enhance medical care and reduce costs. In this paper, a new approach based on coactive neuro-fuzzy inference system (CANFIS) was presented for prediction of heart disease. The proposed CANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach which is then integrated with genetic algorithm to diagnose the presence of the disease. The performances of the CANFIS model were evaluated in terms of training performances and classification accuracies and the results showed that the proposed CANFIS model has great potential in predicting the heart disease.
Abstract: Owing to extensive use of hydrogen in refining or
petrochemical units, it is essential to manage hydrogen network in
order to make the most efficient utilization of hydrogen. On the other
hand, hydrogen is an important byproduct not properly used through
petrochemical complexes and mostly sent to the fuel system. A few
works have been reported in literature to improve hydrogen network
for petrochemical complexes. In this study a comprehensive analysis
is carried out on petrochemical units using a modified automated
targeting technique which is applied to determine the minimum
hydrogen consumption. Having applied the modified targeting
method in two petrochemical cases, the results showed a significant
reduction in required fresh hydrogen.
Abstract: Image restoration involves elimination of noise. Filtering techniques were adopted so far to restore images since last five decades. In this paper, we consider the problem of image restoration degraded by a blur function and corrupted by random noise. A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction methods. The proposed method, which makes use of an a priori noise model, has been evaluated on various types of images. Bayesian based algorithms and technique of image processing have been described and substantiated with experimentation using MATLAB.
Abstract: Human amniotic membrane (HAM) is a useful
biological material for the reconstruction of damaged ocular surface.
The processing and preservation of HAM is critical to prevent the
patients undergoing amniotic membrane transplant (AMT) from cross
infections. For HAM preparation human placenta is obtained after an
elective cesarean delivery. Before collection, the donor is screened
for seronegativity of HCV, Hbs Ag, HIV and Syphilis. After
collection, placenta is washed in balanced salt solution (BSS) in
sterile environment. Amniotic membrane is then separated from the
placenta as well as chorion while keeping the preparation in BSS.
Scrapping of HAM is then carried out manually until all the debris is
removed and clear transparent membrane is acquired. Nitrocellulose
membrane filters are then placed on the stromal side of HAM, cut
around the edges with little membrane folded towards other side
making it easy to separate during surgery. HAM is finally stored in
solution of glycerine and Dulbecco-s Modified Eagle Medium
(DMEM) in 1:1 ratio containing antibiotics. The capped borosil vials
containing HAM are kept at -80°C until use. This vial is thawed to
room temperature and opened under sterile operation theatre
conditions at the time of surgery.
Abstract: Partial Discharge measurement is a very important
means of assessing the integrity of insulation systems in a High
Voltage apparatus. In compressed gas insulation systems, floating
particles can initiate partial discharge activities which adversely
affect the working of insulation. Partial Discharges below the
inception voltage also plays a crucial in damaging the integrity of
insulation over a period of time. This paper discusses the effect of
loose and fixed Copper and Nichrome wire particles on the PD
characteristics in SF6-N2 (10:90) gas mixtures at a pressure of
0.4MPa. The Partial Discharge statistical parameters and their
correlation to the observed results are discussed.
Abstract: The objective this study was to characterize and
develop anthropomorphic liver phantoms in tomography hepatic
procedures for quality control and improvement professionals in
nuclear medicine. For the conformation of the anthropomorphic
phantom was used in plaster and acrylic. We constructed three
phantoms representing processes with liver cirrhosis. The phantoms
were filled with 99mTc diluted with water to obtain the scintigraphic
images. Tomography images were analyzed anterior and posterior
phantom representing a body with a greater degree cirrhotic. It was
noted that the phantoms allow the acquisition of images similar to
real liver with cirrhosis. Simulations of hemangiomas may contribute
to continued professional education of nuclear medicine, on the
question of image acquisition, allowing of the study parameters such
of the matrix, energy window and count statistics.
Abstract: In the present paper, the three-dimensional
temperature field of tool is determined during the machining and
compared with experimental work on C45 workpiece using carbide
cutting tool inserts. During the metal cutting operations, high
temperature is generated in the tool cutting edge which influence on
the rate of tool wear. Temperature is most important characteristic of
machining processes; since many parameters such as cutting speed,
surface quality and cutting forces depend on the temperature and high
temperatures can cause high mechanical stresses which lead to early
tool wear and reduce tool life. Therefore, considerable attention is
paid to determine tool temperatures. The experiments are carried out
for dry and orthogonal machining condition. The results show that
the increase of tool temperature depends on depth of cut and
especially cutting speed in high range of cutting conditions.
Abstract: Physiological activity of the pineal gland with specific
responses in the reproductive territory may be interpreted by
monitoring the process parameters used in poultry practice in
different age batches of laying hens. As biological material were
used 105 laying hens, clinically healthy, belonging to ALBO SL-
2000 hybrid, raised on ground, from which blood samples were taken
at the age of 12 and 28 weeks. The haematological examinations
were concerned to obtain the total number of erythrocytes and
leukocytes and the main erythrocyte constant (RBC, PCV, MCV,
MCH, MCHC and WBC). The results allow the interpretation of the
reproductive status through the dynamics of the presented values.
Abstract: In this paper, we investigated vector control of an induction machine taking into account discretization problems of the command. In the purpose to show how to include in a discrete model of this current control and with rotor time constant update. The results of simulation obtained are very satisfaisant. That was possible thanks to the good choice of the values of the parameters of the regulators used which shows, the founded good of the method used, for the choice of the parameters of the discrete regulators. The simulation results are presented at the end of this paper.
Abstract: Shot boundary detection is a fundamental step for the organization of large video data. In this paper, we propose a new method for video gradual shots detection and classification, using advantages of fractal analysis and AIS-based classifier. Proposed features are “vertical intercept" and “fractal dimension" of each frame of videos which are computed using Fourier transform coefficients. We also used a classifier based on Clonal Selection Algorithm. We have carried out our solution and assessed it according to the TRECVID2006 benchmark dataset.
Abstract: Many factors affect the success of Machine Learning
(ML) on a given task. The representation and quality of the instance
data is first and foremost. If there is much irrelevant and redundant
information present or noisy and unreliable data, then knowledge
discovery during the training phase is more difficult. It is well known
that data preparation and filtering steps take considerable amount of
processing time in ML problems. Data pre-processing includes data
cleaning, normalization, transformation, feature extraction and
selection, etc. The product of data pre-processing is the final training
set. It would be nice if a single sequence of data pre-processing
algorithms had the best performance for each data set but this is not
happened. Thus, we present the most well know algorithms for each
step of data pre-processing so that one achieves the best performance
for their data set.
Abstract: Classes on creativity, innovation, and entrepreneurship
are becoming quite popular at universities throughout the world.
However, it is not easy for business students to get involved to
innovative activities, especially patent application. The present study
investigated how to enhance business students- intention to participate
in innovative activities and which incentives universities should
consider. A 22-item research scale was used, and confirmatory factor
analysis was conducted to verify its reliability and validity. Multiple
regression and discriminant analyses were also conducted. The results
demonstrate the effect of growth-need strength on innovative behavior
and indicate that the theory of planned behavior can explain and
predict business students- intention to participate in innovative
activities. Additionally, the results suggest that applying our proposed
model in practice would effectively strengthen business students-
intentions to engage in innovative activities.
Abstract: Wireless Sensor Network (WSN) comprises of sensor
nodes which are designed to sense the environment, transmit sensed
data back to the base station via multi-hop routing to reconstruct
physical phenomena. Since physical phenomena exists significant
overlaps between temporal redundancy and spatial redundancy, it is
necessary to use Redundancy Suppression Algorithms (RSA) for sensor
node to lower energy consumption by reducing the transmission
of redundancy. A conventional algorithm of RSAs is threshold-based
RSA, which sets threshold to suppress redundant data. Although
many temporal and spatial RSAs are proposed, temporal-spatial RSA
are seldom to be proposed because it is difficult to determine when
to utilize temporal or spatial RSAs. In this paper, we proposed a
novel temporal-spatial redundancy suppression algorithm, Codebookbase
Redundancy Suppression Mechanism (CRSM). CRSM adopts
vector quantization to generate a codebook, which is easily used to
implement temporal-spatial RSA. CRSM not only achieves power
saving and reliability for WSN, but also provides the predictability
of network lifetime. Simulation result shows that the network lifetime
of CRSM outperforms at least 23% of that of other RSAs.