Abstract: Linearization of graph embedding has been emerged
as an effective dimensionality reduction technique in pattern
recognition. However, it may not be optimal for nonlinearly
distributed real world data, such as face, due to its linear nature. So, a
kernelization of graph embedding is proposed as a dimensionality
reduction technique in face recognition. In order to further boost the
recognition capability of the proposed technique, the Fisher-s
criterion is opted in the objective function for better data
discrimination. The proposed technique is able to characterize the
underlying intra-class structure as well as the inter-class separability.
Experimental results on FRGC database validate the effectiveness of
the proposed technique as a feature descriptor.
Abstract: One of the most important aspects expected from an
ERP system is to mange user\administrator manual documents
dynamically. Since an ERP package is frequently changed during its
implementation in customer sites, it is often needed to add new
documents and/or apply required changes to existing documents in
order to cover new or changed capabilities. The worse is that since
these changes occur continuously, the corresponding documents
should be updated dynamically; otherwise, implementing the ERP
package in the organization encounters serious risks. In this paper, we
propose a new architecture which is based on the agent oriented
vision and supplies the dynamic document generation expected from
ERP systems using several independent but cooperative agents.
Beside the dynamic document generation which is the main issue of
this paper, the presented architecture will address some aspects of
intelligence and learning capabilities existing in ERP.
Abstract: The group invariant solution for Prandtl-s boundary layer equations for an incompressible fluid governing the flow in radial free, wall and liquid jets having finite fluid velocity at the orifice are investigated. For each jet a symmetry is associated with the conserved vector that was used to derive the conserved quantity for the jet elsewhere. This symmetry is then used to construct the group invariant solution for the third-order partial differential equation for the stream function. The general form of the group invariant solution for radial jet flows is derived. The general form of group invariant solution and the general form of the similarity solution which was obtained elsewhere are the same.
Abstract: In this paper, we present an innovative scheme of
blindly extracting message bits from an image distorted by an attack.
Support Vector Machine (SVM) is used to nonlinearly classify the
bits of the embedded message. Traditionally, a hard decoder is used
with the assumption that the underlying modeling of the Discrete
Cosine Transform (DCT) coefficients does not appreciably change.
In case of an attack, the distribution of the image coefficients is
heavily altered. The distribution of the sufficient statistics at the
receiving end corresponding to the antipodal signals overlap and a
simple hard decoder fails to classify them properly. We are
considering message retrieval of antipodal signal as a binary
classification problem. Machine learning techniques like SVM is
used to retrieve the message, when certain specific class of attacks is
most probable. In order to validate SVM based decoding scheme, we
have taken Gaussian noise as a test case. We generate a data set using
125 images and 25 different keys. Polynomial kernel of SVM has
achieved 100 percent accuracy on test data.
Abstract: High voltage generators are being subject to higher
voltage rating and are being designed to operate in harsh conditions.
Stator windings are the main component of generators in which
Electrical, magnetical and thermal stresses remain major failures for
insulation degradation accelerated aging. A large number of
generators failed due to stator winding problems, mainly insulation
deterioration. Insulation degradation assessment plays vital role in the
asset life management. Mostly the stator failure is catastrophic
causing significant damage to the plant. Other than generation loss,
stator failure involves heavy repair or replacement cost. Electro
thermal analysis is the main characteristic for improvement design of
stator slot-s insulation. Dielectric parameters such as insulation
thickness, spacing, material types, geometry of winding and slot are
major design consideration. A very powerful method available to
analyze electro thermal performance is Finite Element Method
(FEM) which is used in this paper. The analysis of various stator coil
and slot configurations are used to design the better dielectric system
to reduce electrical and thermal stresses in order to increase the
power of generator in the same volume of core. This paper describes
the process used to perform classical design and improvement
analysis of stator slot-s insulation.
Abstract: In this study, it is investigated the stability boundary of
Functionally Graded (FG) panel under the heats and supersonic
airflows. Material properties are assumed to be temperature
dependent, and a simple power law distribution is taken. First-order
shear deformation theory (FSDT) of plate is applied to model the
panel, and the von-Karman strain- displacement relations are
adopted to consider the geometric nonlinearity due to large
deformation. Further, the first-order piston theory is used to model the
supersonic aerodynamic load acting on a panel and Rayleigh damping
coefficient is used to present the structural damping. In order to find a
critical value of the speed, linear flutter analysis of FG panels is
performed. Numerical results are compared with the previous works,
and present results for the temperature dependent material are
discussed in detail for stability boundary of the panel with various
volume fractions, and aerodynamic pressures.
Abstract: The aim of this study was to establish the relationship between the principles of Educational Sport and the objectives of Physical Education in two brasilian laws: National Curriculum Guidelines (PCNs) for the Elementary and Middle School Levels and the Guidelines and Basis Legislation (LDB). The method used was the survey analysis in order to determine the practices present in, or the opinions of, a specific population. The instrument used in this research was a questionnaire. After a broad review of the bibliography and according to the methodological procedures, the aim was to set the relationships between the Principles of Educational Sport and the objectives of Physical Education, according to the Brazilian Law (LDB) and National Curriculum Guidelines (PCNs) in a table made under the analysis of a group of specialists. As the relation between the principles of Educational Sport and the objectives of School Physical Education have shown, we can state that School Physical Education has gained pedagogical security for the potential use of Educational Sport as part of its contents.
Abstract: Multiple criteria decision making (MCDM) is an approach to ranking the solutions and finding the best one when two or more solutions are provided. In this study, MCDM approach is proposed to select the most suitable scheduling rule of robotic flexible assembly cells (RFACs). Two MCDM approaches, Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are proposed for solving the scheduling rule selection problem. The AHP method is employed to determine the weights of the evaluation criteria, while the TOPSIS method is employed to obtain final ranking order of scheduling rules. Four criteria are used to evaluate the scheduling rules. Also, four scheduling policies of RFAC are examined to choose the most appropriate one for this purpose. A numerical example illustrates applications of the suggested methodology. The results show that the methodology is practical and works in RFAC settings.
Abstract: This paper presents an exact pruning algorithm with
adaptive pruning interval for general dynamic neural networks
(GDNN). GDNNs are artificial neural networks with internal dynamics.
All layers have feedback connections with time delays to the
same and to all other layers. The structure of the plant is unknown, so
the identification process is started with a larger network architecture
than necessary. During parameter optimization with the Levenberg-
Marquardt (LM) algorithm irrelevant weights of the dynamic neural
network are deleted in order to find a model for the plant as
simple as possible. The weights to be pruned are found by direct
evaluation of the training data within a sliding time window. The
influence of pruning on the identification system depends on the
network architecture at pruning time and the selected weight to be
deleted. As the architecture of the model is changed drastically during
the identification and pruning process, it is suggested to adapt the
pruning interval online. Two system identification examples show
the architecture selection ability of the proposed pruning approach.
Abstract: Bangla Vowel characterization determines the spectral properties of Bangla vowels for efficient synthesis as well as recognition of Bangla vowels. In this paper, Bangla vowels in isolated word have been analyzed based on speech production model within the framework of Analysis-by-Synthesis. This has led to the extraction of spectral parameters for the production model in order to produce different Bangla vowel sounds. The real and synthetic spectra are compared and a weighted square error has been computed along with the error in the formant bandwidths for efficient representation of Bangla vowels. The extracted features produced good representation of targeted Bangla vowel. Such a representation also plays essential role in low bit rate speech coding and vocoders.
Abstract: Several numerical schemes utilizing central difference
approximations have been developed to solve the Goursat problem.
However, in a recent years compact discretization methods which
leads to high-order finite difference schemes have been used since it
is capable of achieving better accuracy as well as preserving certain
features of the equation e.g. linearity. The basic idea of the new
scheme is to find the compact approximations to the derivative terms
by differentiating centrally the governing equations. Our primary
interest is to study the performance of the new scheme when applied
to two Goursat partial differential equations against the traditional
finite difference scheme.
Abstract: Calcium [Ca2+] is an important second messenger
which plays an important role in signal transduction. There are
several parameters that affect its concentration profile like buffer
source etc. The effect of stationary immobile buffer on Ca2+
concentration has been incorporated which is a very important
parameter needed to be taken into account in order to make the
model more realistic. Interdependence of all the important parameters
like diffusion coefficient and influx over [Ca2+] profile has been
studied. Model is developed in the form of advection diffusion
equation together with buffer concentration. A program has been
developed using finite volume method for the entire problem and
simulated on an AMD-Turion 32-bit machine to compute the
numerical results.
Abstract: Let S be an ordered semigroup. In this paper we first introduce the concepts of (∈,∈ ∨q)-fuzzy ideals, (∈,∈ ∨q)-fuzzy bi-ideals and (∈,∈ ∨q)-fuzzy generalized bi-ideals of an ordered semigroup S, and investigate their related properties. Furthermore, we also define the upper and lower parts of fuzzy subsets of an ordered semigroup S, and investigate the properties of (∈,∈ ∨q)-fuzzy ideals of S. Finally, characterizations of regular ordered semigroups and intra-regular ordered semigroups by means of the lower part of (∈ ,∈ ∨q)-fuzzy left ideals, (∈,∈ ∨q)-fuzzy right ideals and (∈,∈ ∨q)- fuzzy (generalized) bi-ideals are given.
Abstract: Saturated hydraulic conductivity is one of the soil
hydraulic properties which is widely used in environmental studies
especially subsurface ground water. Since, its direct measurement is
time consuming and therefore costly, indirect methods such as
pedotransfer functions have been developed based on multiple linear
regression equations and neural networks model in order to estimate
saturated hydraulic conductivity from readily available soil
properties e.g. sand, silt, and clay contents, bulk density, and organic
matter. The objective of this study was to develop neural networks
(NNs) model to estimate saturated hydraulic conductivity from
available parameters such as sand and clay contents, bulk density,
van Genuchten retention model parameters (i.e. r
θ , α , and n) as well
as effective porosity. We used two methods to calculate effective
porosity: : (1) eff s FC φ =θ -θ , and (2) inf φ =θ -θ eff s , in which s
θ is
saturated water content, FC θ is water content retained at -33 kPa
matric potential, and inf θ is water content at the inflection point.
Total of 311 soil samples from the UNSODA database was divided
into three groups as 187 for the training, 62 for the validation (to
avoid over training), and 62 for the test of NNs model. A commercial
neural network toolbox of MATLAB software with a multi-layer
perceptron model and back propagation algorithm were used for the
training procedure. The statistical parameters such as correlation
coefficient (R2), and mean square error (MSE) were also used to
evaluate the developed NNs model. The best number of neurons in
the middle layer of NNs model for methods (1) and (2) were
calculated 44 and 6, respectively. The R2 and MSE values of the test
phase were determined for method (1), 0.94 and 0.0016, and for
method (2), 0.98 and 0.00065, respectively, which shows that method
(2) estimates saturated hydraulic conductivity better than method (1).
Abstract: Application of Expert System in the area of agriculture would take the form of Integrated Crop Management decision aids and would encompass water management, fertilizer management, crop protection systems and identification of implements. In order to remain competitive, the modern farmer often relies on agricultural specialists and advisors to provide information for decision-making. An expert system normally composed of a knowledge base (information, heuristics, etc.), inference engine (analyzes knowledge base), and end user interface (accepting inputs, generating outputs). Software named 'CROP-9-DSS' incorporating all modern features like, graphics, photos, video clippings etc. has been developed. This package will aid as a decision support system for identification of pest and diseases with control measures, fertilizer recommendation system, water management system and identification of farm implements for leading crops of Kerala (India) namely Coconut, Rice, Cashew, Pepper, Banana, four vegetables like Amaranthus, Bhindi, Brinjal and Cucurbits. 'CROP-9-DSS' will act as an expert system to agricultural officers, scientists in the field of agriculture and extension workers for decision-making and help them in suggesting suitable recommendations.
Abstract: In this paper, we introduce an effective strategy for
subgoal division and ordering based upon recursive subgoals and
combine this strategy with a genetic-based planning approach. This
strategy can be applied to domains with conjunctive goals. The main
idea is to recursively decompose a goal into a set of serializable
subgoals and to specify a strict ordering among the subgoals.
Empirical results show that the recursive subgoal strategy reduces the
size of the search space and improves the quality of solutions to
planning problems.
Abstract: In this paper, Economic Order Quantity (EOQ) based model for non-instantaneous Weibull distribution deteriorating items with power demand pattern is presented. In this model, the holding cost per unit of the item per unit time is assumed to be an increasing linear function of time spent in storage. Here the retailer is allowed a trade-credit offer by the supplier to buy more items. Also in this model, shortages are allowed and partially backlogged. The backlogging rate is dependent on the waiting time for the next replenishment. This model aids in minimizing the total inventory cost by finding the optimal time interval and finding the optimal order quantity. The optimal solution of the model is illustrated with the help of numerical examples. Finally sensitivity analysis and graphical representations are given to demonstrate the model.
Abstract: Visual attention allows user to select the most relevant
information to ongoing behaviour. This paper presents a study on; i)
the performance of people measurements, ii) accurateness of people
measurement of the peaks that correspond to chemical quantities
from the Magnetic Resonance Spectroscopy (MRS) graphs and iii)
affects of people measurements to the algorithm-based diagnosis.
Participant-s eye-movement was recorded using eye-tracker tool
(Eyelink II). This experiment involves three participants for
examining 20 MRS graphs to estimate the peaks of chemical
quantities which indicate the abnormalities associated with
Cerebellar Tumours (CT). The status of each MRS is verified by
using decision algorithm. Analysis involves determination of
humans-s eye movement pattern in measuring the peak of
spectrograms, scan path and determining the relationship of
distributions of fixation durations with the accuracy of measurement.
In particular, the eye-tracking data revealed which aspects of the
spectrogram received more visual attention and in what order they
were viewed. This preliminary investigation provides a proof of
concept for use of the eye tracking technology as the basis for
expanded CT diagnosis.
Abstract: A mathematical model based on a mass and energy
balance for the combustion in a cement rotary kiln was developed.
The model was used to investigate the impact of replacing about
45 % of the primary coal energy by different alternative fuels.
Refuse derived fuel, waste wood, solid hazardous waste and liquid
hazardous waste were used in the modeling. The results showed that
in order to keep the kiln temperature unchanged, and thereby
maintain the required clinker quality, the production capacity had to
be reduced by 1-15 %, depending on the fuel type. The reason for the
reduction is increased exhaust gas flow rates caused by the fuel
characteristics. The model, which has been successfully validated in a
full-scale experiment, was also used to show that the negative impact
on the production capacity can be avoided if a relatively small part of
the combustion air is replaced by pure oxygen.
Abstract: The concept of e-government has begun to spread among countries. It is based on the use of information communication technology (ICT) to fully utilize government resources, as well as to provide government services to citizens, investors and foreigners. Critical factors are the factors that are determined by the senior management of each organization; the success or failure of the organization depends on the effective implementation of critical factors. These factors vary from one organization to another according to their activity, size and functions. It is very important that organizations identify them in order to avoid the risk of implementing initiatives that may fail to work, while simultaneously exploiting opportunities that may succeed in working. The main focus of this paper is to investigate the majority of critical success factors (CSFs) associated with the implementation of e-government projects. This study concentrates on both technical and nontechnical factors. This paper concludes by listing the majority of CSFs relating to successful e-government implementation in Bahrain.