Abstract: This paper describes part of a project about Learningby-
Modeling (LbM). Studying complex systems is increasingly
important in teaching and learning many science domains. Many
features of complex systems make it difficult for students to develop
deep understanding. Previous research indicates that involvement
with modeling scientific phenomena and complex systems can play a
powerful role in science learning. Some researchers argue with this
view indicating that models and modeling do not contribute to
understanding complexity concepts, since these increases the
cognitive load on students. This study will investigate the effect of
different modes of involvement in exploring scientific phenomena
using computer simulation tools, on students- mental model from the
perspective of structure, behavior and function. Quantitative and
qualitative methods are used to report about 121 freshmen students
that engaged in participatory simulations about complex phenomena,
showing emergent, self-organized and decentralized patterns. Results
show that LbM plays a major role in students' concept formation
about complexity concepts.
Abstract: The primary objective of this paper was to construct a
“kinematic parameter-independent modeling of three-axis machine
tools for geometric error measurement" technique. Improving the
accuracy of the geometric error for three-axis machine tools is one of
the machine tools- core techniques. This paper first applied the
traditional method of HTM to deduce the geometric error model for
three-axis machine tools. This geometric error model was related to the
three-axis kinematic parameters where the overall errors was relative
to the machine reference coordinate system. Given that the
measurement of the linear axis in this model should be on the ideal
motion axis, there were practical difficulties. Through a measurement
method consolidating translational errors and rotational errors in the
geometric error model, we simplified the three-axis geometric error
model to a kinematic parameter-independent model. Finally, based on
the new measurement method corresponding to this error model, we
established a truly practical and more accurate error measuring
technique for three-axis machine tools.
Abstract: Unified Modeling language (UML) is one of the
important modeling languages used for the visual representation of
the research problem. In the present paper, UML model is designed
for the Instruction pipeline which is used for the evaluation of the
instructions of software programs. The class and sequence diagrams
are designed & performance is evaluated for instructions of a sample
program through a case study.
Abstract: Yeast cells live in a constantly changing environment that requires the continuous adaptation of their genomic program in order to sustain their homeostasis, survive and proliferate. Due to the advancement of high throughput technologies, there is currently a large amount of data such as gene expression, gene deletion and protein-protein interactions for S. Cerevisiae under various environmental conditions. Mining these datasets requires efficient computational methods capable of integrating different types of data, identifying inter-relations between different components and inferring functional groups or 'modules' that shape intracellular processes. This study uses computational methods to delineate some of the mechanisms used by yeast cells to respond to environmental changes. The GRAM algorithm is first used to integrate gene expression data and ChIP-chip data in order to find modules of coexpressed and co-regulated genes as well as the transcription factors (TFs) that regulate these modules. Since transcription factors are themselves transcriptionally regulated, a three-layer regulatory cascade consisting of the TF-regulators, the TFs and the regulated modules is subsequently considered. This three-layer cascade is then modeled quantitatively using artificial neural networks (ANNs) where the input layer corresponds to the expression of the up-stream transcription factors (TF-regulators) and the output layer corresponds to the expression of genes within each module. This work shows that (a) the expression of at least 33 genes over time and for different stress conditions is well predicted by the expression of the top layer transcription factors, including cases in which the effect of up-stream regulators is shifted in time and (b) identifies at least 6 novel regulatory interactions that were not previously associated with stress-induced changes in gene expression. These findings suggest that the combination of gene expression and protein-DNA interaction data with artificial neural networks can successfully model biological pathways and capture quantitative dependencies between distant regulators and downstream genes.
Abstract: Cement, the most widely used construction material
is very brittle and characterized by low tensile strength and strain
capacity. Macro to nano fibers are added to cement to provide
tensile strength and ductility to it. Carbon Nanotube (CNT), one of
the nanofibers, has proven to be a promising reinforcing material in
the cement composites because of its outstanding mechanical
properties and its ability to close cracks at the nano level. The
experimental investigations for CNT reinforced cement is costly,
time consuming and involves huge number of trials. Mathematical
modeling of CNT reinforced cement can be done effectively and
efficiently to arrive at the mechanical properties and to reduce the
number of trials in the experiments. Hence, an attempt is made to
numerically study the effective mechanical properties of CNT
reinforced cement numerically using Representative Volume
Element (RVE) method. The enhancement in its mechanical
properties for different percentage of CNTs is studied in detail.
Abstract: This paper gives an overview of the mapping
mechanism of SEAM-a methodology for the automatic generation of
knowledge models and its mapping onto Java codes. It discusses the
rules that will be used to map the different components in the
knowledge model automatically onto Java classes, properties and
methods. The aim of developing this mechanism is to help in the
creation of a prototype which will be used to validate the knowledge
model which has been generated automatically. It will also help to
link the modeling phase with the implementation phase as existing
knowledge engineering methodologies do not provide for proper
guidelines for the transition from the knowledge modeling phase to
development phase. This will decrease the development overheads
associated to the development of Knowledge Based Systems.
Abstract: One of the best ways for achievement of conventional
vehicle changing to hybrid case is trustworthy simulation result and
using of driving realities. For this object, in this paper, at first sevendegree-
of-freedom dynamical model of vehicle will be shown. Then
by using of statically model of engine, gear box, clutch, differential,
electrical machine and battery, the hybrid automobile modeling will
be down and forward simulation of vehicle for pedals to wheels
power transformation will be obtained. Then by design of a fuzzy
controller and using the proper rule base, fuel economy and
regenerative braking will be marked. Finally a series of
MATLAB/SIMULINK simulation results will be proved the
effectiveness of proposed structure.
Abstract: A minimal complexity version of component mode
synthesis is presented that requires simplified computer
programming, but still provides adequate accuracy for modeling
lower eigenproperties of large structures and their transient
responses. The novelty is that a structural separation into components
is done along a plane/surface that exhibits rigid-like behavior, thus
only normal modes of each component is sufficient to use, without
computing any constraint, attachment, or residual-attachment modes.
The approach requires only such input information as a few (lower)
natural frequencies and corresponding undamped normal modes of
each component. A novel technique is shown for formulation of
equations of motion, where a double transformation to generalized
coordinates is employed and formulation of nonproportional damping
matrix in generalized coordinates is shown.
Abstract: Due to the three- dimensional flow pattern interacting with bed material, the process of local scour around bridge piers is complex. Modeling 3D flow field and scour hole evolution around a bridge pier is more feasible nowadays because the computational cost and computational time have significantly decreased. In order to evaluate local flow and scouring around a bridge pier, a completely three-dimensional numerical model, SSIIM program, was used. The model solves 3-D Navier-Stokes equations and a bed load conservation equation. The model was applied to simulate local flow and scouring around a bridge pier in a large natural river with four piers. Computation for 1 day of flood condition was carried out to predict the maximum local scour depth. The results show that the SSIIM program can be used efficiently for simulating the scouring in natural rivers. The results also showed that among the various turbulence models, the k-ω model gives more reasonable results.
Abstract: In this paper a mixed method by combining an evolutionary and a conventional technique is proposed for reduction of Single Input Single Output (SISO) continuous systems into Reduced Order Model (ROM). In the conventional technique, the mixed advantages of Mihailov stability criterion and continued Fraction Expansions (CFE) technique is employed where the reduced denominator polynomial is derived using Mihailov stability criterion and the numerator is obtained by matching the quotients of the Cauer second form of Continued fraction expansions. Then, retaining the numerator polynomial, the denominator polynomial is recalculated by an evolutionary technique. In the evolutionary method, the recently proposed Differential Evolution (DE) optimization technique is employed. DE method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. The proposed method is illustrated through a numerical example and compared with ROM where both numerator and denominator polynomials are obtained by conventional method to show its superiority.
Abstract: The method of modeling is the key technology for
digital mockup (DMU). Based upon the developing for mechanical
product DMU, the theory, method and approach for virtual
environment (VE) and virtual object (VO) were studied. This paper
has expounded the design goal and architecture of DMU system,
analyzed the method of DMU application, and researched the general
process of physics modeling and behavior modeling.
Abstract: National Biodiversity Database System (NBIDS) has
been developed for collecting Thai biodiversity data. The goal of this
project is to provide advanced tools for querying, analyzing,
modeling, and visualizing patterns of species distribution for
researchers and scientists. NBIDS data record two types of datasets:
biodiversity data and environmental data. Biodiversity data are
specie presence data and species status. The attributes of biodiversity
data can be further classified into two groups: universal and projectspecific
attributes. Universal attributes are attributes that are common
to all of the records, e.g. X/Y coordinates, year, and collector name.
Project-specific attributes are attributes that are unique to one or a
few projects, e.g., flowering stage. Environmental data include
atmospheric data, hydrology data, soil data, and land cover data
collecting by using GLOBE protocols. We have developed webbased
tools for data entry. Google Earth KML and ArcGIS were used
as tools for map visualization. webMathematica was used for simple
data visualization and also for advanced data analysis and
visualization, e.g., spatial interpolation, and statistical analysis.
NBIDS will be used by park rangers at Khao Nan National Park, and
researchers.
Abstract: Endovascular aneurysm repair is a new and minimally invasive repair for patients with abdominal aortic aneurysm (AAA). This method has potential advantages that are incomparable with other repair methods. However, the enlargement of aneurysm in the absence of endoleak, which is known as endotension, may occur as one of post-operative compliances of this method. Typically, endotension is mainly as a result of pressure transmitted to aneurysm sac by endovascular installed graft. After installation of graft the aneurysm sac reduces significantly but remains non-zero. There are some factors which affect this pressure transmitted. In this study, the geometry features of installed vascular graft have been considered. It is inferred that graft neck angle and iliac bifurcation angle are two factors which can affect the drag force on graft and consequently the pressure transmitted to aneurysm.
Abstract: Simulation of the flow and sedimentation process in
the reservoir dams can be made by two methods of physical and mathematical modeling. The study area was within a region which
ranged from the Jelogir hydrometric station to the Karkheh reservoir
dam aimed at investigating the effects of stream tubes on the
GSTARS-3 model behavior. The methodologies was to run the model based on 5 stream tubes in order to observe the influence of
each scenario on longitudinal profiles, cross-section, flow velocity and bed load sediment size. Results further suggest that the use of
two stream tubes or more which result in the semi-two-dimensional
model will yield relatively closer results to the observational data
than a singular stream tube modeling. Moreover, the results of
modeling with three stream tubes shown to yield a relatively close
results with the observational data. The overall conclusion of the paper is with applying various stream tubes; it would be possible to yield a significant influence on the modeling behavior Vis-a Vis the bed load sediment size.
Abstract: The modeling of sound radiation is of fundamental importance for understanding the propagation of acoustic waves and, consequently, develop mechanisms for reducing acoustic noise. The propagation of acoustic waves, are involved in various phenomena such as radiation, absorption, transmission and reflection. The radiation is studied through the linear equation of the acoustic wave that is obtained through the equation for the Conservation of Momentum, equation of State and Continuity. From these equations, is the Helmholtz differential equation that describes the problem of acoustic radiation. In this paper we obtained the solution of the Helmholtz differential equation for an infinite cylinder in a pulsating through free and homogeneous. The analytical solution is implemented and the results are compared with the literature. A numerical formulation for this problem is obtained using the Boundary Element Method (BEM). This method has great power for solving certain acoustical problems in open field, compared to differential methods. BEM reduces the size of the problem, thereby simplifying the input data to be worked and reducing the computational time used.
Abstract: The System Identification problem looks for a
suitably parameterized model, representing a given process. The
parameters of the model are adjusted to optimize a performance
function based on error between the given process output and
identified process output. The linear system identification field is
well established with many classical approaches whereas most of
those methods cannot be applied for nonlinear systems. The problem
becomes tougher if the system is completely unknown with only the
output time series is available. It has been reported that the
capability of Artificial Neural Network to approximate all linear and
nonlinear input-output maps makes it predominantly suitable for the
identification of nonlinear systems, where only the output time series
is available. [1][2][4][5]. The work reported here is an attempt to
implement few of the well known algorithms in the context of
modeling of nonlinear systems, and to make a performance
comparison to establish the relative merits and demerits.
Abstract: Radiofrequency (RF) lesioning of nerves have been commonly used to alleviate chronic pain, where RF current preventing transmission of pain signals through the nerve by heating the nerve causing the pain. There are some factors that affect the temperature distribution and the nerve lesion size, one of these factors is the inhomogeneities in the tissue medium. Our objective is to calculate the temperature distribution and the nerve lesion size in an inhomogeneous medium surrounding the RF electrode. A two 3-D finite element models are used to compare the temperature distribution in the homogeneous and inhomogeneous medium. Also the effect of temperature-dependent electric conductivity on maximum temperature and lesion size is observed. Results show that the presence of an inhomogeneous medium around the RF electrode has a valuable effect on the temperature distribution and lesion size. The dependency of electric conductivity on tissue temperature increased lesion size.
Abstract: Avalanche release of snow has been modeled in the present studies. Snow is assumed to be represented by semi-solid and the governing equations have been studied from the concept of continuum approach. The dynamical equations have been solved for two different zones [starting zone and track zone] by using appropriate initial and boundary conditions. Effect of density (ρ), Eddy viscosity (η), Slope angle (θ), Slab depth (R) on the flow parameters have been observed in the present studies. Numerical methods have been employed for computing the non linear differential equations. One of the most interesting and fundamental innovation in the present studies is getting initial condition for the computation of velocity by numerical approach. This information of the velocity has obtained through the concept of fracture mechanics applicable to snow. The results on the flow parameters have found to be in qualitative agreement with the published results.
Abstract: Some of the polycyclic aromatic hydrocarbons (PAHs)
are the strongest known carcinogens compounds; the majority of
them are mostly produced by the incomplete combustion of fossil
fuels; Motor vehicles are a significant source of polycyclic aromatic
hydrocarbon (PAH) where diesel emission is one of the main sources
of such compounds available in the ambient air. There is a big
concern about the increasing concentration of PAHs in the
environment. Researchers are trying to explore optimal methods to
reduce those pollutants and improve the quality of air. Water blended
fuel is one of the possible approaches to reduce emission of PAHs
from the combustion of diesel in urban and domestic vehicles. In this
work a modeling study was conducted using CHEMKIN-PRO
software to simulate spray combustion at similar diesel engine
conditions. Surrogate fuel of (80 % n-heptane and 20 % toluene) was
used due to detailed kinetic and thermodynamic data needed for
modeling is available for this kind of fuel but not available for diesel.
An emulsified fuel with 3, 5, 8, 10 and 20 % water by volume is used
as an engine feed for this study. The modeling results show that water
has a significant effect on reducing engine soot and PAHs precursors
formation up to certain extent.
Abstract: The anti-lock braking systems installed on vehicles
for safe and effective braking, are high-order nonlinear and timevariant.
Using fuzzy logic controllers increase efficiency of such
systems, but impose a high computational complexity as well. The
main concept introduced by this paper is reducing computational
complexity of fuzzy controllers by deploying problem-solution data
structure. Unlike conventional methods that are based on
calculations, this approach is based on data oriented modeling.