Abstract: Overall cost is a significant consideration in any
decision-making process. Although many studies were carried out on
overall cost in construction, little has treated the uncertainties of real
life cycle development. On the basis of several case studies, a
feedback process was performed on the historical data of studied
buildings. This process enabled to identify some factors causing
uncertainty during the operational period. As a result, the research
proposes a new method for assessing the overall cost during a part of
the building-s life cycle taking account of the building actual value,
its end-of-life value and the influence of the identified life cycle
uncertainty factors. The findings are a step towards a higher level of
reliability in overall cost evaluation taking account of some usually
unexpected uncertainty factors.
Abstract: Requirement engineering has been the subject of large
volume of researches due to the significant role it plays in the
software development life cycle. However, dynamicity of software
industry is much faster than advances in requirements engineering
approaches. Therefore, this paper aims to systematically review and
evaluate the current research in requirement engineering and identify
new research trends and direction in this field. In addition, various
research methods associated with the Evaluation-based techniques
and empirical study are highlighted for the requirements engineering
field. Finally, challenges and recommendations on future directions
research are presented based on the research team observations
during this study.
Abstract: The aim of this research is to determine how preservice Turkish teachers perceive themselves in terms of problem solving skills. Students attending Department of Turkish Language Teaching of Gazi University Education Faculty in 2005-2006 academic year constitute the study group (n= 270) of this research in which survey model was utilized. Data were obtained by Problem Solving Inventory developed by Heppner & Peterson and Personal Information Form. Within the settings of this research, Cronbach Alpha reliability coefficient of the scale was found as .87. Besides, reliability coefficient obtained by split-half technique which splits odd and even numbered items of the scale was found as r=.81 (Split- Half Reliability). The findings of the research revealed that preservice Turkish teachers were sufficiently qualified on the subject of problem solving skills and statistical significance was found in favor of male candidates in terms of “gender" variable. According to the “grade" variable, statistical significance was found in favor of 4th graders.
Abstract: In recent years, the number of natural disasters in Laos has a trend to increase, especially the disaster of flood. To make a flood plan risk management in the future, it is necessary to understand and analyze the characteristics of the rainfall and Mekong River level data. To reduce the damage, this paper presents the flood risk analysis in Luangprabang and Vientiane, the prefecture of Laos. In detail, the relationship between the rainfall and the Mekong River level has evaluated and appropriate countermeasure for flood was discussed.
Abstract: This paper proposed high level feature for online Lao handwritten recognition. This feature must be high level enough so that the feature is not change when characters are written by different persons at different speed and different proportion (shorter or longer stroke, head, tail, loop, curve). In this high level feature, a character is divided in to sequence of curve segments where a segment start where curve reverse rotation (counter clockwise and clockwise). In each segment, following features are gathered cumulative change in direction of curve (- for clockwise), cumulative curve length, cumulative length of left to right, right to left, top to bottom and bottom to top ( cumulative change in X and Y axis of segment). This feature is simple yet robust for high accuracy recognition. The feature can be gather from parsing the original time sampling sequence X, Y point of the pen location without re-sampling. We also experiment on other segmentation point such as the maximum curvature point which was widely used by other researcher. Experiments results show that the recognition rates are at 94.62% in comparing to using maximum curvature point 75.07%. This is due to a lot of variations of turning points in handwritten.
Abstract: In this paper, we show that the association of the PI
regulators for the speed and stator currents with a control strategy
using the linearization by state feedback for an induction machine
without speed sensor, and with an adaptation of the rotor resistance.
The rotor speed is estimated by using the model reference adaptive
system approach (MRAS). This method consists of using two
models: The first is the reference model and the second is an
adjustable one in which two components of the stator flux, obtained
from the measurement of the currents and stator voltages are
estimated. The estimated rotor speed is then obtained by canceling
the difference between stator-flux of the reference model and those
of the adjustable one. Satisfactory results of simulation are obtained
and discussed in this paper to highlight the proposed approach.
Abstract: This work is to study a roll of the fluctuating density
gradient in the compressible flows for the computational fluid dynamics
(CFD). A new anisotropy tensor with the fluctuating density
gradient is introduced, and is used for an invariant modeling technique
to model the turbulent density gradient correlation equation derived
from the continuity equation. The modeling equation is decomposed
into three groups: group proportional to the mean velocity, and that
proportional to the mean strain rate, and that proportional to the mean
density. The characteristics of the correlation in a wake are extracted
from the results by the two dimensional direct simulation, and shows
the strong correlation with the vorticity in the wake near the body.
Thus, it can be concluded that the correlation of the density gradient
is a significant parameter to describe the quick generation of the
turbulent property in the compressible flows.
Abstract: This paper gives an overview of a deep drawing
process by pressurized liquid medium separated from the sheet by a
rubber diaphragm. Hydroforming deep drawing processing of sheet
metal parts provides a number of advantages over conventional
techniques. It generally increases the depth to diameter ratio possible
in cup drawing and minimizes the thickness variation of the drawn
cup. To explore the deformation mechanism, analytical and
numerical simulations are used for analyzing the drawing process of
an AA6061-T4 blank. The effects of key process parameters such as
coefficient of friction, initial thickness of the blank and radius
between cup wall and flange are investigated analytically and
numerically. The simulated results were in good agreement with the
results of the analytical model. According to finite element
simulations, the hydroforming deep drawing method provides a more
uniform thickness distribution compared to conventional deep
drawing and decreases the risk of tearing during the process.
Abstract: The intrusion detection problem has been frequently studied, but intrusion detection methods are often based on a single point of view, which always limits the results. In this paper, we introduce a new intrusion detection model based on the combination of different current methods. First we use a notion of distance to unify the different methods. Second we combine these methods using the Pearson correlation coefficients, which measure the relationship between two methods, and we obtain a combined distance. If the combined distance is greater than a predetermined threshold, an intrusion is detected. We have implemented and tested the combination model with two different public data sets: the data set of masquerade detection collected by Schonlau & al., and the data set of program behaviors from the University of New Mexico. The results of the experiments prove that the combination model has better performances.
Abstract: In this paper, fully developed flow and heat transfer of
viscoelastic materials in curved ducts with square cross section under
constant heat flux have been investigated. Here, staggered mesh is
used as computational grids and flow and heat transfer parameters
have been allocated in this mesh with marker and cell method.
Numerical solution of governing equations has being performed with
FTCS finite difference method. Furthermore, Criminale-Eriksen-
Filbey (CEF) constitutive equation has being used as viscoelastic
model. CEF constitutive equation is a suitable model for studying
steady shear flow of viscoelastic materials which is able to model
both effects of the first and second normal stress differences. Here, it
is shown that the first and second normal stresses differences have
noticeable and inverse effect on secondary flows intensity and mean
Nusselt number which is the main novelty of current research.
Abstract: The Deoxyribonucleic Acid (DNA) which is a doublestranded helix of nucleotides consists of: Adenine (A), Cytosine (C), Guanine (G) and Thymine (T). In this work, we convert this genetic code into an equivalent digital signal representation. Applying a wavelet transform, such as Haar wavelet, we will be able to extract details that are not so clear in the original genetic code. We compare between different organisms using the results of the Haar wavelet Transform. This is achieved by using the trend part of the signal since the trend part bears the most energy of the digital signal representation. Consequently, we will be able to quantitatively reconstruct different biological families.
Abstract: Trends in business intelligence, e-commerce and
remote access make it necessary and practical to store data in
different ways on multiple systems with different operating systems.
As business evolve and grow, they require efficient computerized
solution to perform data update and to access data from diverse
enterprise business applications. The objective of this paper is to
demonstrate the capability of DTS [1] as a database solution for
automatic data transfer and update in solving business problem. This
DTS package is developed for the sales of variety of plants and
eventually expanded into commercial supply and landscaping
business. Dimension data modeling is used in DTS package to
extract, transform and load data from heterogeneous database
systems such as MySQL, Microsoft Access and Oracle that
consolidates into a Data Mart residing in SQL Server. Hence, the
data transfer from various databases is scheduled to run automatically
every quarter of the year to review the efficient sales analysis.
Therefore, DTS is absolutely an attractive solution for automatic data
transfer and update which meeting today-s business needs.
Abstract: Potatoes are a good source of carotenoids, which are lipophilic compounds synthesized in plastids from isoprenoids. The aim of this research was to determine the content of carotenoids in relationship with the colour of organically and conventionally cultivated potato genotypes before and after period of storage. In cooperation with the State Priekuli Plant Breeding Institute (Latvia), six potato genotypes were studied: 'Agrie dzeltenie', 'Prelma', 'Imanta', 'S-03135-10', 'S-99108-8' and 'S-01063-5'. All the genotypes were cultivated under three different conditions: organically and conventionally (two conditions). The content of carotenoids was determined by using spectrophotometer and the colour – L*a*b* system. The results of current research show that after the period of storage, carotenoid amount has increased and in conventionally cultivated potatoes it varies from 228.514 to 552.434 μg 100 g-1 while in organically cultivated potato genotypes – from 45.485 to 662.699 μg 100 g-1 FW. Colour of potato flesh was changing during storage.
Abstract: In this paper, stabilization of an Active Magnetic Bearing (AMB) system with varying rotor speed using Sliding Mode Control (SMC) technique is considered. The gyroscopic effect inherited in the system is proportional to rotor speed in which this nonlinearity effect causes high system instability as the rotor speed increases. Also, transformation of the AMB dynamic model into a new class of uncertain system shows that this gyroscopic effect lies in the mismatched part of the system matrix. Moreover, the current gain parameter is allowed to be varied in a known bound as an uncertainty in the input matrix. SMC design method is proposed in which the sufficient condition that guarantees the global exponential stability of the reduced-order system is represented in Linear Matrix Inequality (LMI). Then, a new chattering-free control law is established such that the system states are driven to reach the switching surface and stay on it thereafter. The performance of the controller applied to the AMB model is demonstrated through simulation works under various system conditions.
Abstract: Fuzzy C-means Clustering algorithm (FCM) is a
method that is frequently used in pattern recognition. It has the
advantage of giving good modeling results in many cases, although,
it is not capable of specifying the number of clusters by itself. In
FCM algorithm most researchers fix weighting exponent (m) to a
conventional value of 2 which might not be the appropriate for all
applications. Consequently, the main objective of this paper is to use
the subtractive clustering algorithm to provide the optimal number of
clusters needed by FCM algorithm by optimizing the parameters of
the subtractive clustering algorithm by an iterative search approach
and then to find an optimal weighting exponent (m) for the FCM
algorithm. In order to get an optimal number of clusters, the iterative
search approach is used to find the optimal single-output Sugenotype
Fuzzy Inference System (FIS) model by optimizing the
parameters of the subtractive clustering algorithm that give minimum
least square error between the actual data and the Sugeno fuzzy
model. Once the number of clusters is optimized, then two
approaches are proposed to optimize the weighting exponent (m) in
the FCM algorithm, namely, the iterative search approach and the
genetic algorithms. The above mentioned approach is tested on the
generated data from the original function and optimal fuzzy models
are obtained with minimum error between the real data and the
obtained fuzzy models.
Abstract: Flow through micro and mini channels requires relatively
high driving pressure due to the large fluid pressure drop
through these channels. Consequently the forces acting on the walls of
the channel due to the fluid pressure are also large. Due to these forces
there are displacement fields set up in the solid substrate containing
the channels. If the movement of the substrate is constrained at some
points, then stress fields are established in the substrate. On the other
hand, if the deformation of the channel shape is sufficiently large
then its effect on the fluid flow is important to be calculated. Such
coupled fluid-solid systems form a class of problems known as fluidstructure
interactions. In the present work a co-located finite volume
discretization procedure on unstructured meshes is described for
solving fluid-structure interaction type of problems. A linear elastic
solid is assumed for which the effect of the channel deformation
on the flow is neglected. Thus the governing equations for the
fluid and the solid are decoupled and are solved separately. The
procedure is validated by solving two benchmark problems, one from
fluid mechanics and another from solid mechanics. A fluid-structure
interaction problem of flow through a U-shaped channel embedded
in a plate is solved.
Abstract: In this paper, we give a certain decomposition of the
coefficient matrix of the fully fuzzy linear system (FFLS) to obtain
a simple algorithm for solving these systems. The new algorithm
can solve FFLS in a smaller computing process. We will illustrate
our method by solving some examples.
Abstract: Titanium alloys like Ti-6Al-2Sn-4Zr-6Mo (Ti-
6246) are widely used in aerospace applications. Component
manufacturing, however, is difficult and expensive as their
machinability is extremely poor. A thorough understanding of the
chip formation process is needed to improve related metal cutting
operations.In the current study, orthogonal cutting experiments have
been performed and theresulting chips were analyzed by optical
microscopy and scanning electron microscopy.Chips from aTi-
6246ingot were produced at different cutting speeds and cutting
depths. During the experiments, depending of the cutting conditions,
continuous or segmented chips were formed. Narrow, highly
deformed and grain oriented zones, the so-called shear zone,
separated individual segments. Different material properties have
been measured in the shear zones and the segments.
Abstract: In this paper, the effects of the restoring force device on the response of a space frame structure resting on sliding type of bearing with a restoring force device is studied. The NS component of the El - Centro earthquake and harmonic ground acceleration is considered for earthquake excitation. The structure is modeled by considering six-degrees of freedom (three translations and three rotations) at each node. The sliding support is modeled as a fictitious spring with two horizontal degrees of freedom. The response quantities considered for the study are the top floor acceleration, base shear, bending moment and base displacement. It is concluded from the study that the displacement of the structure reduces by the use of the restoring force device. Also, the peak values of acceleration, bending moment and base shear also decreases. The simulation results show the effectiveness of the developed and proposed method.
Abstract: This paper reports a new pattern recognition approach for face recognition. The biological model of light receptors - cones and rods in human eyes and the way they are associated with pattern vision in human vision forms the basis of this approach. The functional model is simulated using CWD and WPD. The paper also discusses the experiments performed for face recognition using the features extracted from images in the AT & T face database. Artificial Neural Network and k- Nearest Neighbour classifier algorithms are employed for the recognition purpose. A feature vector is formed for each of the face images in the database and recognition accuracies are computed and compared using the classifiers. Simulation results show that the proposed method outperforms traditional way of feature extraction methods prevailing for pattern recognition in terms of recognition accuracy for face images with pose and illumination variations.