Abstract: This research is part of a broad program aimed at
advancing the science and technology involved in the rescue and
rehabilitation of oiled wildlife. One aspect of this research involves
the use of oil-sequestering magnetic particles for the removal of
contaminants from plumage – so-called “magnetic cleansing". This
treatment offers a number of advantages over conventional
detergent-based methods including portability - which offers the
possibility of providing a “quick clean" to the animal upon first
encounter in the field. This could be particularly advantageous
when the contaminant is toxic and/or corrosive and/or where there
is a delay in transporting the victim to a treatment centre. The
method could also be useful as part of a stabilization protocol when
large numbers of affected animals are awaiting treatment. This
presentation describes the design, development and testing of a
prototype field kit for providing a “quick clean" to contaminated
wildlife in the field.
Abstract: Information and communication technology (ICT) has
become, within a very short time, one of the basic building blocks of
modern society. Many countries now understanding the importance
of ICT and mastering the basic skills and concepts of it as part of the
core of education. Organizations, experts and practitioners in the
education sector increasingly recognizing the importance of ICT in
supporting educational improvement and reform. This paper
addresses the convergence of ICT and education. When two
technologies are converging to each other, together they will generate
some great opportunities and challenges. This paper focuses on these
issues. In introduction section, it explains the ICT, education, and
ICT-enhanced education. In next section it describes need of ICT in
education, relationship between ICT skills and education, and stages
of teaching learning process. The next two sections describe
opportunities and challenges in integrating ICT in education. Finally
the concluding section summaries the idea and its usefulness.
Abstract: Understanding proteins functions is a major goal in
the post-genomic era. Proteins usually work in context of other
proteins and rarely function alone. Therefore, it is highly relevant to
study the interaction partners of a protein in order to understand its
function. Machine learning techniques have been widely applied to
predict protein-protein interactions. Kernel functions play an
important role for a successful machine learning technique. Choosing
the appropriate kernel function can lead to a better accuracy in a
binary classifier such as the support vector machines. In this paper,
we describe a Bayesian kernel for the support vector machine to
predict protein-protein interactions. The use of Bayesian kernel can
improve the classifier performance by incorporating the probability
characteristic of the available experimental protein-protein
interactions data that were compiled from different sources. In
addition, the probabilistic output from the Bayesian kernel can assist
biologists to conduct more research on the highly predicted
interactions. The results show that the accuracy of the classifier has
been improved using the Bayesian kernel compared to the standard
SVM kernels. These results imply that protein-protein interaction can
be predicted using Bayesian kernel with better accuracy compared to
the standard SVM kernels.
Abstract: State-based testing is frequently used in software testing. Test data generation is one of the key issues in software testing. A properly generated test suite may not only locate the errors in a software system, but also help in reducing the high cost associated with software testing. It is often desired that test data in the form of test sequences within a test suite can be automatically generated to achieve required test coverage. This paper proposes an Ant Colony Optimization approach to test data generation for the state-based software testing.
Abstract: This paper presents methodologies for developing an
intelligent CAD system assisting in analysis and design of
reconfigurable special machines. It describes a procedure for
determining feasibility of utilizing these machines for a given part
and presents a model for developing an intelligent CAD system. The
system analyzes geometrical and topological information of the given
part to determine possibility of the part being produced by
reconfigurable special machines from a technical point of view. Also
feasibility of the process from a economical point of view is
analyzed. Then the system determines proper positioning of the part
considering details of machining features and operations needed.
This involves determination of operation types, cutting tools and the
number of working stations needed. Upon completion of this stage
the overall layout of the machine and machining equipment required
are determined.
Abstract: Graphene-metal contact resistance limits the performance of graphene-based electrical devices. In this work, we have fabricated both graphene field-effect transistors (GFET) and transfer length measurement (TLM) test devices with titanium contacts. The purpose of this work is to compare the contact resistances that can be numerically extracted from the GFETs and measured from the TLM structures. We also provide a brief review of the work done in the field to solve the contact resistance problem.
Abstract: Using a texture database, a statistical estimation of
spring-back was conducted in this study on the basis of statistical
analysis. Both spring-back in bending deformation and experimental
data related to the crystal orientation show significant dispersion.
Therefore, a probabilistic statistical approach was established for the
proper quantification of these values. Correlation was examined
among the parameters F(x) of spring-back, F(x) of the buildup fraction
to three orientations after 92° bending, and F(x) at an as-received part
on the basis of the three-parameter Weibull distribution. Consequent
spring-back estimation using a texture database yielded excellent
estimates compared with experimental values.
Abstract: This research aims to study employment trends in
printing industry for prepress support by Suan Sunandha University
Fund. The objectives of this research are to explain the trends of the
employment in Thai Printing Industry for prepress in Bangkok and
the description of different personnel that prepress entrepreneur need
and also the problems of employment.
The population of prepress entrepreneurs is about 100
organizations in the area of Bangkok. The questionnaires has been
taken and analyzed with SPSS program by using the average
percentage and standard deviation.
This research is multiple case studies. The conceptual framework
is developed on the basis of the open systems theory.
The research result show that
1. The most of prepress entrepreneur have trend to choose the
employee by any sex, the age 25-29 years old, bachelor degree
and have 1-2 years experience.
2. The most problems are the understanding in job,
communication/relation and the understanding in new
technology.
3. The trends aims to employment in 1-3 years have 57.8% for
prepress industry in Bangkok.
This research suggests that:
1. Thai printing industry for prepress in Bangkok need quality
employee that expert in printing technology.
2. Prepress entrepreneur should have agreement to development
with university for practice the employee.
3. Prepress entrepreneur should support personal to fulfill the
knowledge.
Abstract: For high-speed control of robots, a good knowledge of system modelling is necessary to obtain the desired bandwidth. In this paper, we present a cartesian robot with a pan/tilt unit in end-effector (5 dof). This robot is implemented with powerful direct drive AC induction machines. The dynamic model, parameter identification and model validation of the robot are studied (including actuators). This work considers the cartesian robot coupled and non linear (contrary to normal considerations for this type of robots). The mechanical and control architecture proposed in this paper is efficient for industrial and research application in which high speed, well known model and very high accuracy are required.
Abstract: This paper reviews various approaches that have been
used for the modeling and simulation of large-scale engineering
systems and determines their appropriateness in the development of a
RICS modeling and simulation tool. Bond graphs, linear graphs,
block diagrams, differential and difference equations, modeling
languages, cellular automata and agents are reviewed. This tool
should be based on linear graph representation and supports symbolic
programming, functional programming, the development of noncausal
models and the incorporation of decentralized approaches.
Abstract: Wheeled Mobile Robots (WMRs) are built with their
Wheels- drive machine, Motors. Depend on their desire design of
WMR, Technicians made used of DC Motors for motion control. In
this paper, the author would like to analyze how to choose DC motor
to be balance with their applications of especially for WMR.
Specification of DC Motor that can be used with desire WMR is to
be determined by using MATLAB Simulink model. Therefore, this
paper is mainly focus on software application of MATLAB and
Control Technology. As the driving system of DC motor, a
Peripheral Interface Controller (PIC) based control system is
designed including the assembly software technology and H-bridge
control circuit. This Driving system is used to drive two DC gear
motors which are used to control the motion of WMR. In this
analyzing process, the author mainly focus the drive system on
driving two DC gear motors that will control with Differential Drive
technique to the Wheeled Mobile Robot . For the design analysis of
Motor Driving System, PIC16F84A is used and five inputs of sensors
detected data are tested with five ON/OFF switches. The outputs of
PIC are the commands to drive two DC gear motors, inputs of Hbridge
circuit .In this paper, Control techniques of PIC
microcontroller and H-bridge circuit, Mechanism assignments of
WMR are combined and analyzed by mainly focusing with the
“Modeling and Simulink of DC Motor using MATLAB".
Abstract: System identification is the process of creating
models of dynamic process from input- output signals. The aim of
system identification can be identified as “ to find a model with
adjustable parameters and then to adjust them so that the predicted
output matches the measured output". This paper presents a method
of modeling and simulating with system identification to achieve the
maximum fitness for transformation function. First by using
optimized KLM equivalent circuit for PVDF piezoelectric transducer
and assuming different inputs including: sinuside, step and sum of
sinusides, get the outputs, then by using system identification
toolbox in MATLAB, we estimate the transformation function from
inputs and outputs resulted in last program. Then compare the fitness
of transformation function resulted from using ARX,OE(Output-
Error) and BJ(Box-Jenkins) models in system identification toolbox
and primary transformation function form KLM equivalent circuit.
Abstract: One of the most common practices for strengthening
the reinforced concrete structures is the application of FRP (Fiber
Reinforce Plastic) sheets to increase the flexural and shear strengths
of the member. The elastic modulus of FRP is considerably higher
than that of concrete. This will result in debonding between the FRP
sheets and concrete surface. With conventional surface preparation of
concrete, the ultimate capacity of the FRP sheets can hardly be
achieved. New methods for preparation of the bonding surface have
shown improvements in reducing the premature debonding of FRP
sheets from concrete surface. The present experimental study focuses
on the application of grooving method to postpone debonding of the
FRP sheets attached to the side faces of concrete beams for shear
strengthening. Comparison has also been made with conventional
surface preparation method. This study clearly shows the efficiency
of grooving method compared to surface preparation method, in
preventing the debonding phenomenon and in increasing the load
carrying capacity of FRP.
Abstract: Fast forecasting of stock market prices is very important for
strategic planning. In this paper, a new approach for fast forecasting of
stock market prices is presented. Such algorithm uses new high speed
time delay neural networks (HSTDNNs). The operation of these
networks relies on performing cross correlation in the frequency
domain between the input data and the input weights of neural
networks. It is proved mathematically and practically that the number
of computation steps required for the presented HSTDNNs is less
than that needed by traditional time delay neural networks
(TTDNNs). Simulation results using MATLAB confirm the
theoretical computations.
Abstract: In recent years, the research in wireless sensor
network has increased steadily, and many studies were focusing on
reducing energy consumption of sensor nodes to extend their lifetimes.
In this paper, the issue of energy consumption is investigated and two
adaptive mechanisms are proposed to extend the network lifetime.
This study uses high-energy-first scheme to determine cluster heads
for data transmission. Thus, energy consumption in each cluster is
balanced and network lifetime can be extended. In addition, this study
uses cluster merging and dynamic routing mechanisms to further
reduce energy consumption during data transmission. The simulation
results show that the proposed method can effectively extend the
lifetime of wireless sensor network, and it is suitable for different base
station locations.
Abstract: In the present study, changes of morphology and
mechanical characteristics in the lumbar vertebrae of the
ovariectomised (OVX) rat were investigated. In previous researches,
there were many studies about morphology like volume fraction and
trabecular thickness based on Micro - Computed Tomography (Micro
- CT). However, detecting and tracking long-term changes in the
trabecular bone of the lumbar vertebrae for the OVX rat were few. For
this study, one female Sprague-Dawley rat was used: an OVX rat. The
4th Lumbar of the OVX rat was subjected to in-vivo micro-CT.
Detecting and tracking long-term changes could be investigated in the
trabecular bone of the lumbar vertebrae for an OVX rat using in-vivo
micro-CT. An OVX rat was scanned at week 0 (just before surgery), at
week 4, at week 8, week 16, week 22 and week 56 after surgery. Finite
element (FE) analysis was used to investigate mechanical
characteristics of the lumbar vertebrae for an OVX rat. When the OVX
rat (at week 56) was compared with the OVX rat (at week 0), volume
fraction was decreased by 80% and effective modulus was decreased
by 75%.
Abstract: The hospital and the health-care center of a
community, as a place for people-s life-care and health-care settings,
must provide more and better services for patients or residents. After
Establishing Electronic Medical Record (EMR) system -which is a
necessity- in the hospital, providing pervasive services is a further
step. Our objective in this paper is to use pervasive computing in a
case study of healthcare, based on EMR database that coordinates
application services over network to form a service environment for
medical and health-care. Our method also categorizes the hospital
spaces into 3 spaces: Public spaces, Private spaces and Isolated
spaces. Although, there are many projects about using pervasive
computing in healthcare, but all of them concentrate on the disease
recognition, designing smart cloths, or provide services only for
patient. The proposed method is implemented in a hospital. The
obtained results show that it is suitable for our purpose.
Abstract: This paper describes studies carried out to investigate
the viability of using wireless cameras as a tool in monitoring
changes in air quality. A camera is used to monitor the change in
colour of a chemically responsive polymer within view of the camera
as it is exposed to varying chemical species concentration levels. The
camera captures this image and the colour change is analyzed by
averaging the RGB values present. This novel chemical sensing
approach is compared with an established chemical sensing method
using the same chemically responsive polymer coated onto LEDs. In
this way, the concentration levels of acetic acid in the air can be
tracked using both approaches. These approaches to chemical plume
tracking have many applications for air quality monitoring.
Abstract: An enhanced particle swarm optimization algorithm
(PSO) is presented in this work to solve the non-convex OPF
problem that has both discrete and continuous optimization variables.
The objective functions considered are the conventional quadratic
function and the augmented quadratic function. The latter model
presents non-differentiable and non-convex regions that challenge
most gradient-based optimization algorithms. The optimization
variables to be optimized are the generator real power outputs and
voltage magnitudes, discrete transformer tap settings, and discrete
reactive power injections due to capacitor banks. The set of equality
constraints taken into account are the power flow equations while the
inequality ones are the limits of the real and reactive power of the
generators, voltage magnitude at each bus, transformer tap settings,
and capacitor banks reactive power injections. The proposed
algorithm combines PSO with Newton-Raphson algorithm to
minimize the fuel cost function. The IEEE 30-bus system with six
generating units is used to test the proposed algorithm. Several cases
were investigated to test and validate the consistency of detecting
optimal or near optimal solution for each objective. Results are
compared to solutions obtained using sequential quadratic
programming and Genetic Algorithms.
Abstract: Years of extensive research in the field of speech
processing for compression and recognition in the last five decades,
resulted in a severe competition among the various methods and
paradigms introduced. In this paper we include the different representations
of speech in the time-frequency and time-scale domains
for the purpose of compression and recognition. The examination of
these representations in a variety of related work is accomplished.
In particular, we emphasize methods related to Fourier analysis
paradigms and wavelet based ones along with the advantages and
disadvantages of both approaches.