Abstract: The gases generated in oil filled transformers can be
used for qualitative determination of incipient faults. The Dissolved
Gas Analysis has been widely used by utilities throughout the world
as the primarily diagnostic tool for transformer maintenance. In this
paper, various Artificial Intelligence Techniques that have been used
by the researchers in the past have been reviewed, some conclusions
have been drawn and a sequential hybrid system has been proposed.
The synergy of ANN and FIS can be a good solution for reliable
results for predicting faults because one should not rely on a single
technology when dealing with real–life applications.
Abstract: This paper deals with condition monitoring of electric switch machine for railway points. Point machine, as a complex electro-mechanical device, switch the track between two alternative routes. There has been an increasing interest in railway safety and the optimal management of railway equipments maintenance, e.g. point machine, in order to enhance railway service quality and reduce system failure. This paper explores the development of Kolmogorov- Smirnov (K-S) test to detect some point failures (external to the machine, slide chairs, fixing, stretchers, etc), while the point machine (inside the machine) is in its proper condition. Time-domain stator Current signatures of normal (healthy) and faulty points are taken by 3 Hall Effect sensors and are analyzed by K-S test. The test is simulated by creating three types of such failures, namely putting a hard stone and a soft stone between stock rail and switch blades as obstacles and also slide chairs- friction. The test has been applied for those three faults which the results show that K-S test can effectively be developed for the aim of other point failures detection, which their current signatures deviate parametrically from the healthy current signature. K-S test as an analysis technique, assuming that any defect has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. This test works based on the null hypothesis that ECDF of target distribution is statistically similar to ECDF of reference distribution. Therefore by comparing a given current signature (as target signal) from unknown switch state to a number of template signatures (as reference signal) from known switch states, it is possible to identify which is the most likely state of the point machine under analysis.
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: Wireless sensor networks are consisted of hundreds or
thousands of small sensors that have limited resources.
Energy-efficient techniques are the main issue of wireless sensor
networks. This paper proposes an energy efficient agent-based
framework in wireless sensor networks. We adopt biologically
inspired approaches for wireless sensor networks. Agent operates
automatically with their behavior policies as a gene. Agent aggregates
other agents to reduce communication and gives high priority to nodes
that have enough energy to communicate. Agent behavior policies are
optimized by genetic operation at the base station. Simulation results
show that our proposed framework increases the lifetime of each node.
Each agent selects a next-hop node with neighbor information and
behavior policies. Our proposed framework provides self-healing,
self-configuration, self-optimization properties to sensor nodes.
Abstract: The construction of a civil structure inside a urban
area inevitably modifies the outdoor microclimate at the building
site. Wind speed, wind direction, air pollution, driving rain, radiation
and daylight are some of the main physical aspects that are subjected
to the major changes. The quantitative amount of these modifications
depends on the shape, size and orientation of the building and on its
interaction with the surrounding environment.The flow field over a
flat roof model building has been numerically investigated in order to
determine two-dimensional CFD guidelines for the calculation of the
turbulent flow over a structure immersed in an atmospheric boundary
layer. To this purpose, a complete validation campaign has been
performed through a systematic comparison of numerical simulations
with wind tunnel experimental data.Several turbulence models and
spatial node distributions have been tested for five different vertical
positions, respectively from the upstream leading edge to the
downstream bottom edge of the analyzed model. Flow field
characteristics in the neighborhood of the building model have been
numerically investigated, allowing a quantification of the capabilities
of the CFD code to predict the flow separation and the extension of
the recirculation regions.The proposed calculations have allowed the
development of a preliminary procedure to be used as a guidance in
selecting the appropriate grid configuration and corresponding
turbulence model for the prediction of the flow field over a twodimensional
roof architecture dominated by flow separation.
Abstract: The morphology, mineralogical and chemical
composition of a low-grade nickel ore from Mpumalanga, South
Africa, were studied by scanning electron microscope (SEM), X-ray
diffraction (XRD) and X-ray fluorescence (XRF), respectively. The
ore was subjected to atmospheric agitation leaching using sulphuric
acid to investigate the effects of acid concentration, leaching
temperature, leaching time and particle size on extraction of nickel
and cobalt. Analyses results indicated the ore to be a saprolitic nickel
laterite belonging to the serpentine group of minerals. Sulphuric acid
was found to be able to extract nickel from the ore. Increased acid
concentration and temperature only produced low amounts of nickel
but improved cobalt extraction. As high as 77.44% Ni was achieved
when leaching a -106+75μm fraction with 4.0M acid concentration at
25oC. The kinetics of nickel leaching from the saprolitic ore were
studied and the activation energy was determined to be 18.16kJ/mol.
This indicated that nickel leaching reaction was diffusion controlled.
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: In this paper, we apply a semismooth active set method to image inpainting. The method exploits primal and dual features of a proposed regularized total variation model, following after the technique presented in [4]. Numerical results show that the method is fast and efficient in inpainting sufficiently thin domains.
Abstract: Modeling of the distributed systems allows us to
represent the whole its functionality. The working system instance
rarely fulfils the whole functionality represented by model; usually
some parts of this functionality should be accessible periodically.
The reporting system based on the Data Warehouse concept seams to
be an intuitive example of the system that some of its functionality is
required only from time to time. Analyzing an enterprise risk
associated with the periodical change of the system functionality, we
should consider not only the inaccessibility of the components
(object) but also their functions (methods), and the impact of such a
situation on the system functionality from the business point of view.
In the paper we suggest that the risk attributes should be estimated
from risk attributes specified at the requirements level (Use Case in
the UML model) on the base of the information about the structure of
the model (presented at other levels of the UML model). We argue
that it is desirable to consider the influence of periodical changes in
requirements on the enterprise risk estimation. Finally, the
proposition of such a solution basing on the UML system model is
presented.
Abstract: In this article, a mathematical programming model
for choosing an optimum portfolio of investments is developed.
The investments are considered as investment projects. The
uncertainties of the real world are associated through fuzzy
concepts for coefficients of the proposed model (i. e. initial
investment costs, profits, resource requirement, and total available
budget). Model has been coded by using LINGO 11.0 solver. The
results of a full analysis of optimistic and pessimistic derivative
models are promising for selecting an optimum portfolio of
projects in presence of uncertainty.
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: Some fast exact algorithms for the maximum weight clique problem have been proposed. Östergard’s algorithm is one of them. Kumlander says his algorithm is faster than it. But we confirmed that the straightforwardly implemented Kumlander’s algorithm is slower than O¨ sterga˚rd’s algorithm. We propose some improvements on Kumlander’s algorithm.
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: 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: This study aimed at assessing whether and to what extent moral judgment and behaviour were: 1. situation-dependent; 2. selectively dependent on cognitive and affective components; 3. influenced by gender and age; 4. reciprocally congruent. In order to achieve these aims, four different types of moral dilemmas were construed and five types of thinking were presented for each of them – representing five possible ways to evaluate the situation. The judgment criteria included selfishness, altruism, sense of justice, and the conflict between selfishness and the two moral issues. The participants were 250 unpaid volunteers (50% male; 50% female) belonging to two age-groups: young people and adults. The study entailed a 2 (gender) x 2 (age-group) x 5 (type of thinking) x 4 (situation) mixed design: the first two variables were betweensubjects, the others were within-subjects. Results have shown that: 1. moral judgment and behaviour are at least partially affected by the type of situations and by interpersonal variables such as gender and age; 2. moral reasoning depends in a similar manner on cognitive and affective factors; 3. there is not a gender polarity between the ethic of justice and the ethic of cure/ altruism; 4. moral reasoning and behavior are perceived as reciprocally congruent even though their congruence decreases with a more objective assessment. Such results were discussed in the light of contrasting theories on morality.
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.