Abstract: In this research work, investigations are carried out on
Continuous Wave (CW) Nd:YAG laser welding system after
preliminary experimentation to understand the influencing parameters
associated with laser welding of AISI 304. The experimental
procedure involves a series of laser welding trials on AISI 304
stainless steel sheets with various combinations of process parameters
like beam power, beam incident angle and beam incident angle. An
industrial 2 kW CW Nd:YAG laser system, available at Welding
Research Institute (WRI), BHEL Tiruchirappalli, is used for
conducting the welding trials for this research. After proper tuning of
laser beam, laser welding experiments are conducted on AISI 304
grade sheets to evaluate the influence of various input parameters on
weld bead geometry i.e. bead width (BW) and depth of penetration
(DOP). From the laser welding results, it is noticed that the beam
power and welding speed are the two influencing parameters on
depth and width of the bead. Three dimensional finite element
simulation of high density heat source have been performed for laser
welding technique using finite element code ANSYS for predicting
the temperature profile of laser beam heat source on AISI 304
stainless steel sheets. The temperature dependent material properties
for AISI 304 stainless steel are taken into account in the simulation,
which has a great influence in computing the temperature profiles.
The latent heat of fusion is considered by the thermal enthalpy of
material for calculation of phase transition problem. A Gaussian
distribution of heat flux using a moving heat source with a conical
shape is used for analyzing the temperature profiles. Experimental
and simulated values for weld bead profiles are analyzed for stainless
steel material for different beam power, welding speed and beam
incident angle. The results obtained from the simulation are
compared with those from the experimental data and it is observed
that the results of numerical analysis (FEM) are in good agreement
with experimental results, with an overall percentage of error
estimated to be within ±6%.
Abstract: Bidding is a very important business function to find
latent contractors of construction projects. Moreover, bid markup is
one of the most important decisions for a bidder to gain a reasonable
profit. Since the bidding system is a complex adaptive system, bidding
agent need a learning process to get more valuable knowledge for a bid,
especially from past public bidding information. In this paper, we
proposed an iterative agent leaning model for bidders to make markup
decisions. A classifier for public bidding information named PIBS is
developed to make full use of history data for classifying new bidding
information. The simulation and experimental study is performed to
show the validity of the proposed classifier. Some factors that affect
the validity of PIBS are also analyzed at the end of this work.
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: 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: 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: 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 objective of this paper is to study the analysis and testing for determining the torsional stiffness of the student formula-s space frame. From past study, the space frame for Chulalongkorn University Student Formula team used in 2011 TSAE Auto Challenge Student Formula in Thailand was designed by considering required mass and torsional stiffness based on the numerical method and experimental method. The numerical result was compared with the experimental results to verify the torsional stiffness of the space frame. It can be seen from the large error of torsional stiffness of 2011 frame that the experimental result can not verify by the numerical analysis due to the different between the numerical model and experimental setting. In this paper, the numerical analysis and experiment of the same 2011 frame model is performed by improving the model setting. The improvement of both numerical analysis and experiment are discussed to confirm that the models from both methods are same. After the frame was analyzed and tested, the results are compared to verify the torsional stiffness of the frame. It can be concluded that the improved analysis and experiments can used to verify the torsional stiffness of the space frame.
Abstract: Today, numerical simulation is a powerful tool to
solve various hydraulic engineering problems. The aim of this
research is numerical solutions of shallow water equations using
finite volume method for Simulations of dam break over wet and dry
bed. In order to solve Riemann problem, Roe-s approximate solver is
used. To evaluate numerical model, simulation was done in 1D and
2D states. In 1D state, two dam break test over dry bed (with and
without friction) were studied. The results showed that Structural
failure around the dam and damage to the downstream constructions
in bed without friction is more than friction bed. In 2D state, two
tests for wet and dry beds were done. Generally in wet bed case,
waves are propagated to canal sides but in dry bed it is not
significant. Therefore, damage to the storage facilities and
agricultural lands in wet bed case is more than in dry bed.
Abstract: In this paper we propose a method for vision systems
to consistently represent functional dependencies between different
visual routines along with relational short- and long-term knowledge
about the world. Here the visual routines are bound to visual properties
of objects stored in the memory of the system. Furthermore,
the functional dependencies between the visual routines are seen
as a graph also belonging to the object-s structure. This graph is
parsed in the course of acquiring a visual property of an object to
automatically resolve the dependencies of the bound visual routines.
Using this representation, the system is able to dynamically rearrange
the processing order while keeping its functionality. Additionally, the
system is able to estimate the overall computational costs of a certain
action. We will also show that the system can efficiently use that
structure to incorporate already acquired knowledge and thus reduce
the computational demand.
Abstract: Breastfeeding is an important concept in the maternal life of a woman. In this paper, we focus on exclusive breastfeeding. Exclusive breastfeeding is the feeding of a baby on no other milk apart from breast milk. This type of breastfeeding is very important during the first six months because it supports optimal growth and development during infancy and reduces the risk of obliterating diseases and problems. Moreover, in Mauritius, exclusive breastfeeding has decreased the incidence and/or severity of diarrhea, lower respiratory infection and urinary tract infection. In this paper, we give an overview of exclusive breastfeeding in Mauritius and the factors influencing it. We further analyze the local practices of exclusive breastfeeding using the Generalized Poisson regression model and the negative-binomial model since the data are over-dispersed.
Abstract: The objective of this paper is to propose an adaptive multi threshold for image segmentation precisely in object detection. Due to the different types of license plates being used, the requirement of an automatic LPR is rather different for each country. The proposed technique is applied on Malaysian LPR application. It is based on Multi Layer Perceptron trained by back propagation. The proposed adaptive threshold is introduced to find the optimum threshold values. The technique relies on the peak value from the graph of the number object versus specific range of threshold values. The proposed approach has improved the overall performance compared to current optimal threshold techniques. Further improvement on this method is in progress to accommodate real time system specification.
Abstract: Solution for the complete removal of carbon
monoxide from the exhaust gases still poses a challenge to the
researchers and this problem is still under development. Modeling for
reduction of carbon monoxide is carried out using heterogeneous
reaction using low cost non-noble metal based catalysts for the
purpose of controlling emissions released to the atmosphere. A
simple one-dimensional model was developed for the monolith using
hopcalite catalyst. The converter is assumed to be an adiabatic
monolith operating under warm-up conditions. The effect of inlet gas
temperatures and catalyst loading on carbon monoxide reduction
during cold start period in the converter is analysed.
Abstract: As networking has become popular, Web-learning
tends to be a trend while designing a tool. Moreover, five-axis
machining has been widely used in industry recently; however, it has
potential axial table colliding problems. Thus this paper aims at
proposing an efficient web-learning collision detection tool on
five-axis machining. However, collision detection consumes heavy
resource that few devices can support, thus this research uses a
systematic approach based on web knowledge to detect collision. The
methodologies include the kinematics analyses for five-axis motions,
separating axis method for collision detection, and computer
simulation for verification. The machine structure is modeled as STL
format in CAD software. The input to the detection system is the
g-code part program, which describes the tool motions to produce the
part surface. This research produced a simulation program with C
programming language and demonstrated a five-axis machining
example with collision detection on web site. The system simulates the
five-axis CNC motion for tool trajectory and detects for any collisions
according to the input g-codes and also supports high-performance
web service benefiting from C. The result shows that our method
improves 4.5 time of computational efficiency, comparing to the
conventional detection method.
Abstract: Atrial Fibrillation is the most common sustained
arrhythmia encountered by clinicians. Because of the invisible
waveform of atrial fibrillation in atrial activation for human, it is
necessary to develop an automatic diagnosis system. 12-Lead ECG
now is available in hospital and is appropriate for using Independent
Component Analysis to estimate the AA period. In this research, we
also adopt a second-order blind identification approach to transform
the sources extracted by ICA to more precise signal and then we use
frequency domain algorithm to do the classification. In experiment,
we gather a significant result of clinical data.
Abstract: A new multi inner stage (MIS) cyclone was designed to
remove the acidic gas and fine particles produced from electronic
industry. To characterize gas flow in MIS cyclone, pressure and
velocity distribution were calculated by means of CFD program. Also,
the flow locus of fine particles and particle removal efficiency were
analyzed by Lagrangian method. When outlet pressure condition was
–100mmAq, the efficiency was the best in this study.
Abstract: Proper management of residues originated from
industrial activities is considered as one of the serious challenges
faced by industrial societies due to their potential hazards to the
environment. Common disposal methods for industrial solid wastes
(ISWs) encompass various combinations of solely management
options, i.e. recycling, incineration, composting, and sanitary
landfilling. Indeed, the procedure used to evaluate and nominate the
best practical methods should be based on environmental, technical,
economical, and social assessments. In this paper an environmentaltechnical
assessment model is developed using analytical network
process (ANP) to facilitate the decision making practice for ISWs
generated at Gilan province, Iran. Using the results of performed
surveys on industrial units located at Gilan, the various groups of
solid wastes in the research area were characterized, and four
different ISW management scenarios were studied. The evaluation
process was conducted using the above-mentioned model in the
Super Decisions software (version 2.0.8) environment. The results
indicates that the best ISW management scenario for Gilan province
is consist of recycling the metal industries residues, composting the
putrescible portion of ISWs, combustion of paper, wood, fabric and
polymeric wastes as well as energy extraction in the incineration
plant, and finally landfilling the rest of the waste stream in addition
with rejected materials from recycling and compost production plants
and ashes from the incineration unit.
Abstract: The phenomenon of global warming or climate
change has led to many environmental issues including higher
atmospheric temperatures, intense precipitation, increased
greenhouse gaseous emissions and increased indoor discomfort.
Studies have shown that bringing nature to the roof such as
constructing green roof and implementing high-reflective roof may
give positive impact in mitigating the effects of global warming and
in increasing thermal comfort sensation inside buildings. However,
no study has been conducted to compare both types of passive roof
treatments in Malaysia in order to increase thermal comfort in
buildings. Therefore, this study is conducted to investigate the effect
of green roof and white painted roof as passive roof treatment in
improving indoor comfort of Malaysian homes. This study uses an
experimental approach in which the measurements of temperatures
are conducted on the case study building. The measurements of
outdoor and indoor environments were conducted on the flat roof
with two different types of roof treatment that are green roof and
white roof. The measurement of existing black bare roof was also
conducted to act as a control for this study.
Abstract: Zero inflated strict arcsine model is a newly developed
model which is found to be appropriate in modeling overdispersed
count data. In this study, we extend zero inflated strict arcsine model
to zero inflated strict arcsine regression model by taking into
consideration the extra variability caused by extra zeros and
covariates in count data. Maximum likelihood estimation method is
used in estimating the parameters for this zero inflated strict arcsine
regression model.
Abstract: In this paper we study the fuzzy c-mean clustering algorithm
combined with principal components method. Demonstratively
analysis indicate that the new clustering method is well rather than
some clustering algorithms. We also consider the validity of clustering
method.
Abstract: In this paper is presented a Geographic Information System (GIS) approach in order to qualify and monitor the broadband lines in efficient way. The methodology used for interpolation is the Delaunay Triangular Irregular Network (TIN). This method is applied for a case study in ISP Greece monitoring 120,000 broadband lines.