Abstract: Interactive web-based computer simulations are
needed by the medical community to replicate the experience of
surgical procedures as closely and realistically as possible without
the need to practice on corpses, animals and/or plastic models. In this
paper, we offer a review on current state of the research on
simulations of surgical threads, identify future needs and present our
proposed plans to meet them. Our goal is to create a physics-based
simulator, which will predict the behavior of surgical thread when
subjected to conditions commonly encountered during surgery. To
that end, we will i) develop three dimensional finite element models
based on the Cosserat theory of elasticity ii) test and feedback results
with the medical community and iii) develop a web-based user
interface to run/command our simulator and visualize the results. The
impacts of our research are that i) it will contribute to the
development of a new generation of training for medical school
students and ii) the simulator will be useful to expert surgeons in
developing new, better and less risky procedures.
Abstract: This paper presents a technique for diagnosis of the abdominal aorta aneurysm in magnetic resonance imaging (MRI) images. First, our technique is designed to segment the aorta image in MRI images. This is a required step to determine the volume of aorta image which is the important step for diagnosis of the abdominal aorta aneurysm. Our proposed technique can detect the volume of aorta in MRI images using a new external energy for snakes model. The new external energy for snakes model is calculated from Law-s texture. The new external energy can increase the capture range of snakes model efficiently more than the old external energy of snakes models. Second, our technique is designed to diagnose the abdominal aorta aneurysm by Bayesian classifier which is classification models based on statistical theory. The feature for data classification of abdominal aorta aneurysm was derived from the contour of aorta images which was a result from segmenting of our snakes model, i.e., area, perimeter and compactness. We also compare the proposed technique with the traditional snakes model. In our experiment results, 30 images are trained, 20 images are tested and compared with expert opinion. The experimental results show that our technique is able to provide more accurate results than 95%.
Abstract: This paper present the study carried out of accident
analysis, black spot study and to develop accident predictive models
based on the data collected at rural roadway, Federal Route 50 (F050)
Malaysia. The road accident trends and black spot ranking were
established on the F050. The development of the accident prediction
model will concentrate in Parit Raja area from KM 19 to KM 23.
Multiple non-linear regression method was used to relate the discrete
accident data with the road and traffic flow explanatory variable. The
dependent variable was modeled as the number of crashes namely
accident point weighting, however accident point weighting have
rarely been account in the road accident prediction Models. The result
show that, the existing number of major access points, without traffic
light, rise in speed, increasing number of Annual Average Daily
Traffic (AADT), growing number of motorcycle and motorcar and
reducing the time gap are the potential contributors of increment
accident rates on multiple rural roadway.
Abstract: Medical compression bandages are widely used in the
treatment of chronic venous disorder. In order to design effective
compression bandages, researchers have attempted to describe the
interface pressure applied by multi-layer bandages using mathematical
models. This paper reports on the work carried out to
compare and validate the mathematical models used to describe the
interface pressure applied by multi-layer bandages. Both analytical
and experimental results showed that using simple multiplication
of a number of bandage layers with the pressure applied by one
layer of bandage or ignoring the increase in the limb radius due to
former layers of bandage will result in overestimating the pressure.
Experimental results showed that the mathematical models, which
take into consideration the increase in the limb radius due to former
bandage layers, are more accurate than the one which does not.
Abstract: The purpose of this study is to investigate the capacity
of natural Turkish zeolite for NH4-N removal from landfill leachate.
The effects of modification and initial concentration on the removal
of NH4-N from leachate were also investigated. The kinetics of
adsorption of NH4-N has been discussed using three kinetic models,
i.e., the pseudo-second order model, the Elovich equation, the
intraparticle diffuion model. Kinetic parameters and correlation
coefficients were determined. Equilibrium isotherms for the
adsorption of NH4-N were analyzed by Langmuir, Freundlich and
Tempkin isotherm models. Langmuir isotherm model was found to
best represent the data for NH4-N.
Abstract: Embedded hardware simulator is a valuable computeraided
tool for embedded application development. This paper focuses
on the ARM926EJ-S MMU, builds state transition models and
formally verifies critical properties for the models. The state transition
models include loading instruction model, reading data model, and
writing data model. The properties of the models are described by
CTL specification language, and they are verified in VIS. The results
obtained in VIS demonstrate that the critical properties of MMU are
satisfied in the state transition models. The correct models can be
used to implement the MMU component in our simulator. In the
end of this paper, the experimental results show that the MMU can
successfully accomplish memory access requests from CPU.
Abstract: A dynamic software risk assessment model is
presented. Analogies between dynamic financial analysis and
software risk assessment models are established and based on these
analogies it suggested that dynamic risk model for software projects
is the way to move forward for the risk assessment of software
project. It is shown how software risk assessment change during
different phases of a software project and hence requires a dynamic
risk assessment model to capture these variations. Further evolution
of dynamic financial analysis models is discussed and mapped to the
evolution of software risk assessment models.
Abstract: In automotive systems almost all steps concerning the
calibration of several control systems, e.g., low idle governor or
boost pressure governor, are made with the vehicle because the timeto-
production and cost requirements on the projects do not allow for
the vehicle analysis necessary to build reliable models. Here is
presented a procedure using parametric and NN (neural network)
models that enables the generation of vehicle system models based
on normal ECU engine control unit) vehicle measurements. These
models are locally valid and permit pre and follow-up calibrations so
that, only the final calibrations have to be done with the vehicle.
Abstract: The IFS is a scheme for describing and manipulating complex fractal attractors using simple mathematical models. More precisely, the most popular “fractal –based" algorithms for both representation and compression of computer images have involved some implementation of the method of Iterated Function Systems (IFS) on complete metric spaces. In this paper a new generalized space called Multi-Fuzzy Fractal Space was constructed. On these spases a distance function is defined, and its completeness is proved. The completeness property of this space ensures the existence of a fixed-point theorem for the family of continuous mappings. This theorem is the fundamental result on which the IFS methods are based and the fractals are built. The defined mappings are proved to satisfy some generalizations of the contraction condition.
Abstract: The potential of economically cheaper cellulose
containing natural materials like rice husk was assessed for nickel
adsorption from aqueous solutions. The effects of pH, contact time,
sorbent dose, initial metal ion concentration and temperature on the
uptake of nickel were studied in batch process. The removal of nickel
was dependent on the physico-chemical characteristics of the
adsorbent, adsorbate concentration and other studied process
parameters. The sorption data has been correlated with Langmuir,
Freundlich and Dubinin-Radush kevich (D-R) adsorption models. It
was found that Freundlich and Langmuir isotherms fitted well to the
data. Maximum nickel removal was observed at pH 6.0. The
efficiency of rice husk for nickel removal was 51.8% for dilute
solutions at 20 g L-1 adsorbent dose. FTIR, SEM and EDAX were
recorded before and after adsorption to explore the number and
position of the functional groups available for nickel binding on to
the studied adsorbent and changes in surface morphology and
elemental constitution of the adsorbent. Pseudo-second order model
explains the nickel kinetics more effectively. Reusability of the
adsorbent was examined by desorption in which HCl eluted 78.93%
nickel. The results revealed that nickel is considerably adsorbed on
rice husk and it could be and economic method for the removal of
nickel from aqueous solutions.
Abstract: Group contribution based models are widely used in
industrial applications for its convenience and flexibility. Although a
number of group contribution models have been proposed, there were
certain limitations inherent to those models. Models based on group
contribution excess Gibbs free energy are limited to low pressures and
models based on equation of state (EOS) cannot properly describe
highly nonideal mixtures including acids without introducing
additional modification such as chemical theory. In the present study
new a new approach derived from quantum chemistry have been used
to calculate necessary EOS group interaction parameters. The
COSMO-RS method, based on quantum mechanics, provides a
reliable tool for fluid phase thermodynamics. Benefits of the group
contribution EOS are the consistent extension to hydrogen-bonded
mixtures and the capability to predict polymer-solvent equilibria up to
high pressures. The authors are confident that with a sufficient
parameter matrix the performance of the lattice EOS can be improved
significantly.
Abstract: The results show that the bridge equipped with seismic isolation bearing system shows a high amount of energy dissipation. The purpose of the present study is to analyze the overall performance of continuous curved highway viaducts with different bearing supports, with an emphasis on the effectiveness of seismic isolation based on lead rubber bearing and hedge reaction force bearing system consisted of friction sliding bearing and rubber bearing. The bridge seismic performance has been evaluated on six different cases with six bearing models. The effects of the different arrangement of bearing on the deck superstructure displacements, the seismic damage at the bottom of the piers, movement track at the pier-s top and the total and strain energies absorbed by the structure are evaluated. In conclusion, the results provide sufficient evidence of the effectiveness on the use of seismic isolation on steel curved highway bridges.
Abstract: The mitigation of crop loss due to damaging freezes
requires accurate air temperature prediction models. Previous work
established that the Ward-style artificial neural network (ANN) is a
suitable tool for developing such models. The current research
focused on developing ANN models with reduced average prediction
error by increasing the number of distinct observations used in
training, adding additional input terms that describe the date of an
observation, increasing the duration of prior weather data included in
each observation, and reexamining the number of hidden nodes used
in the network. Models were created to predict air temperature at
hourly intervals from one to 12 hours ahead. Each ANN model,
consisting of a network architecture and set of associated parameters,
was evaluated by instantiating and training 30 networks and
calculating the mean absolute error (MAE) of the resulting networks
for some set of input patterns. The inclusion of seasonal input terms,
up to 24 hours of prior weather information, and a larger number of
processing nodes were some of the improvements that reduced
average prediction error compared to previous research across all
horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or
12.5%, less than the previous model. Prediction MAEs eight and 12
hours ahead improved by 0.17°C and 0.16°C, respectively,
improvements of 7.4% and 5.9% over the existing model at these
horizons. Networks instantiating the same model but with different
initial random weights often led to different prediction errors. These
results strongly suggest that ANN model developers should consider
instantiating and training multiple networks with different initial
weights to establish preferred model parameters.
Abstract: A two dimensional numerical simulation has been
performed for incompressible and compressible fluid flow through
microchannels in slip flow regime. The Navier-Stokes equations have
been solved in conjunction with Maxwell slip conditions for
modeling flow field associated with slip flow regime. The wall
roughness is simulated with triangular microelements distributed on
wall surfaces to study the effects of roughness on fluid flow. Various
Mach and Knudsen numbers are used to investigate the effects of
rarefaction as well as compressibility. It is found that rarefaction has
more significant effect on flow field in microchannels with higher
relative roughness. It is also found that compressibility has more
significant effects on Poiseuille number when relative roughness
increases. In addition, similar to incompressible models the increase
in average fRe is more significant at low Knudsen number flows but
the increase of Poiseuille number duo to relative roughness is sharper
for compressible models. The numerical results have also validated
with some available theoretical and experimental relations and good
agreements have been seen.
Abstract: The Petri net tool INA is a well known tool by the
Petri net community. However, it lacks a graphical environment to
cerate and analyse INA models. Building a modelling tool for the
design and analysis from scratch (for INA tool for example) is
generally a prohibitive task. Meta-Modelling approach is useful to
deal with such problems since it allows the modelling of the
formalisms themselves. In this paper, we propose an approach based
on the combined use of Meta-modelling and Graph Grammars to
automatically generate a visual modelling tool for INA for analysis
purposes. In our approach, the UML Class diagram formalism is
used to define a meta-model of INA models. The meta-modelling
tool ATOM3 is used to generate a visual modelling tool according to
the proposed INA meta-model. We have also proposed a graph
grammar to automatically generate INA description of the
graphically specified Petri net models. This allows the user to avoid
the errors when this description is done manually. Then the INA tool
is used to perform the simulation and the analysis of the resulted INA
description. Our environment is illustrated through an example.
Abstract: Decision Feedback equalizers (DFEs) usually outperform linear equalizers for channels with intersymbol interference. However, the DFE performance is highly dependent on the availability of reliable past decisions. Hence, in coded systems, where reliable decisions are only available after decoding the full block, the performance of the DFE will be affected. A symbol based DFE is a DFE that only uses the decision after the block is decoded. In this paper we derive the optimal settings of both the feedforward and feedback taps of the symbol based equalizer. We present a novel symbol based DFE filterbank, and derive its taps optimal settings. We also show that it outperforms the classic DFE in terms of complexity and/or performance.
Abstract: Steel plate shear walls (SPSWs) in buildings are
known to be an effective means for resisting lateral forces. By using
un-stiffened walls and allowing them to buckle, their energy
absorption capacity will increase significantly due to the postbuckling
capacity. The post-buckling tension field action of SPSWs
can provide substantial strength, stiffness and ductility. This paper
presents the Finite Element Analysis of low yield point (LYP) steel
shear walls. In this shear wall system, the LYP steel plate is used for
the steel panel and conventional structural steel is used for boundary
frames. A series of nonlinear cyclic analyses were carried out to
obtain the stiffness, strength, deformation capacity, and energy
dissipation capacity of the LYP steel shear wall. The effect of widthto-
thickness ratio of steel plate on buckling behavior, and energy
dissipation capacities were studied. Good energy dissipation and
deformation capacities were obtained for all models.
Abstract: There are two common types of operational research techniques, optimisation and metaheuristic methods. The latter may be defined as a sequential process that intelligently performs the exploration and exploitation adopted by natural intelligence and strong inspiration to form several iterative searches. An aim is to effectively determine near optimal solutions in a solution space. In this work, a type of metaheuristics called Ant Colonies Optimisation, ACO, inspired by a foraging behaviour of ants was adapted to find optimal solutions of eight non-linear continuous mathematical models. Under a consideration of a solution space in a specified region on each model, sub-solutions may contain global or multiple local optimum. Moreover, the algorithm has several common parameters; number of ants, moves, and iterations, which act as the algorithm-s driver. A series of computational experiments for initialising parameters were conducted through methods of Rigid Simplex, RS, and Modified Simplex, MSM. Experimental results were analysed in terms of the best so far solutions, mean and standard deviation. Finally, they stated a recommendation of proper level settings of ACO parameters for all eight functions. These parameter settings can be applied as a guideline for future uses of ACO. This is to promote an ease of use of ACO in real industrial processes. It was found that the results obtained from MSM were pretty similar to those gained from RS. However, if these results with noise standard deviations of 1 and 3 are compared, MSM will reach optimal solutions more efficiently than RS, in terms of speed of convergence.
Abstract: In this paper we present, propose and examine
additional membership functions for the Smoothing Transition
Autoregressive (STAR) models. More specifically, we present the
tangent hyperbolic, Gaussian and Generalized bell functions.
Because Smoothing Transition Autoregressive (STAR) models
follow fuzzy logic approach, more fuzzy membership functions
should be tested. Furthermore, fuzzy rules can be incorporated or
other training or computational methods can be applied as the error
backpropagation or genetic algorithm instead to nonlinear squares.
We examine two macroeconomic variables of US economy, the
inflation rate and the 6-monthly treasury bills interest rates.
Abstract: In this paper, estimation of the linear regression
model is made by ordinary least squares method and the
partially linear regression model is estimated by penalized
least squares method using smoothing spline. Then, it is
investigated that differences and similarity in the sum of
squares related for linear regression and partial linear
regression models (semi-parametric regression models). It is
denoted that the sum of squares in linear regression is reduced
to sum of squares in partial linear regression models.
Furthermore, we indicated that various sums of squares in the
linear regression are similar to different deviance statements in
partial linear regression. In addition to, coefficient of the
determination derived in linear regression model is easily
generalized to coefficient of the determination of the partial
linear regression model. For this aim, it is made two different
applications. A simulated and a real data set are considered to
prove the claim mentioned here. In this way, this study is
supported with a simulation and a real data example.