Abstract: According to the conception of personnel
management, human resource management requires efficient use of
human resources. This is ensured by various activities directed
towards the area of management. Among these activities there are for
example the recruitment of employees, development, strengthening
of relations, mutual inspiring, implementation of correct working
processes and systems used by individuals or groups.
Abstract: The recent trend in field oriented control (FOC) is towards the use of sensorless techniques that avoid the use of speed sensor and flux sensor. Sensors are replaced by estimators or observers to minimise the cost and increase the reliability. In this paper an anlyse of perfomance of a MRAS used in sensorless control of induction motors and sensitvity to machine parameters change are studied.
Abstract: The experimental thermal performance of two heat
exchangers in closed-wet cooling tower (CWCT) was investigated in
this study. The test sections are heat exchangers which have multi path
that is used as the entrance of cooling water and are consisting of
bare-type copper tubes between 15.88mm and 19.05mm. The process
fluids are the cooling water that flows from top part of heat exchanger
to bottom side in the inner side of tube, and spray water that flows
gravitational direction in the outer side of it. Air contacts its outer side
of that as it counterflows. Heat and mass transfer coefficients and
cooling capacity were calculated with variations of process fluids,
multi path and different diameter tubes to figure out the performance
of characteristics of CWCT.
The main results were summarized as follows: The results show this
experiment is reliable with values of heat and mass transfer
coefficients comparing to values of correlations. Heat and mass
transfer coefficients and cooling capacity of two paths are higher than
these with one path using 15.88 and 19.05mm tubes. Cooling capacity
per unit volume with 15.88mm tube using one and two paths are
higher than 19.05mm tube due to increase of surface area per unit
volume.
Abstract: This study investigated the presence of polycyclic
aromatic hydrocarbons (PAHs) in the sediments of the Musa Bay
(around the PETZONE coastal area) from Feb 2010 to Jun 2010.
Concentrations of PAHs recorded in the Musa Bay sediments ranged
from 537.89 to 26,659.06 ng/g dry weight with a mean value of
3990.74 ng/g. the highest concentration of PAHs was observed at
station 4, which is located near the aromatic outlet of Imam
Khomeini petrochemical company (station 4: BI-PC Aromatic
effluent outlet) in which its concentration level was more than the
NOAA sediment quality guideline value (ERL= 4022 ng/g dry
weight). Owing to the concentration of PAHs in the study area, its
concentration level was still meet the NOAA sediment quality
guideline value (ERL: 4022 ng/g dry weight); however, according to
the PELq factor, slightly adverse biological effects are associated
with the exposure to PAHs levels in the study area (0.1< PELq= 0.24
> 0.5).
Abstract: School experiences, family bonding and self-concept
had always been a crucial factor in influencing all aspects of a
student-s development. The purpose of this study is to develop and to
validate a priori model of self-concept among students. The study
was tested empirically using Structural Equation Modeling (SEM)
and Confirmatory Factor Analysis (CFA) to validate the structural
model. To address these concerns, 1167 students were randomly
selected and utilized the Cognitive Psycho-Social University of
Malaya instrument (2009).Resulted demonstrated there is indirect
effect from family bonding to self-concept through school
experiences among secondary school students as a mediator. Besides
school experiences, there is a direct effect from family bonding to
self-concept and family bonding to school experiences among
students.
Abstract: Linear cryptanalysis methods are rarely used to improve the security of chaotic stream ciphers. In this paper, we apply linear cryptanalysis to a chaotic stream cipher which was designed by strictly using the basic design criterion of cryptosystem – confusion and diffusion. We show that this well-designed chaos-based stream cipher is still insecure against distinguishing attack. This distinguishing attack promotes the further improvement of the cipher.
Abstract: In this article the influence of higher frequency effects
in addition to a special damper design on the electrical behavior of a
synchronous generator main exciter machine is investigated. On the
one hand these machines are often highly stressed by harmonics from
the bridge rectifier thus facing additional eddy current losses. On the
other hand the switching may cause the excitation of dangerous
voltage peaks in resonant circuits formed by the diodes of the
rectifier and the commutation reactance of the machine. Therefore
modern rotating exciters are treated like synchronous generators
usually modeled with a second order equivalent circuit. Hence the
well known Standstill Frequency Response Test (SSFR) method is
applied to a test machine in order to determine parameters for the
simulation. With these results it is clearly shown that higher
frequencies have a strong impact on the conventional equivalent
circuit model. Because of increasing field displacement effects in the
stranded armature winding the sub-transient reactance is even smaller
than the armature leakage at high frequencies. As a matter of fact this
prevents the algorithm to find an equivalent scheme. This issue is
finally solved using Laplace transfer functions fully describing the
transient behavior at the model ports.
Abstract: Traditional principal components analysis (PCA)
techniques for face recognition are based on batch-mode training
using a pre-available image set. Real world applications require that
the training set be dynamic of evolving nature where within the
framework of continuous learning, new training images are
continuously added to the original set; this would trigger a costly
continuous re-computation of the eigen space representation via
repeating an entire batch-based training that includes the old and new
images. Incremental PCA methods allow adding new images and
updating the PCA representation. In this paper, two incremental
PCA approaches, CCIPCA and IPCA, are examined and compared.
Besides, different learning and testing strategies are proposed and
applied to the two algorithms. The results suggest that batch PCA is
inferior to both incremental approaches, and that all CCIPCAs are
practically equivalent.
Abstract: Permeability reduction induced by asphaltene
precipitation during gas injection is one of the serious problems in
the oil industry. This problem can lead to formation damage and
decrease the oil production rate. In this work, Malaysian light oil
sample has been used to investigate the effect CO2 injection and
Water Alternating Gas (WAG) injection on permeability reduction.
In this work, dynamic core flooding experiments were conducted to
study the effect of CO2 and WAG injection on the amount of
asphaltene precipitated. Core properties after displacement were
inspected for any permeability reduction to study the effect of
asphaltene precipitation on rock properties.
The results showed that WAG injection gave less asphaltene
precipitation and formation damage compared to CO2 injection. The
study suggested that WAG injection can be one of the important
factors of managing asphaltene precipitation.
Abstract: Recent research on seeds of bio-diesel plants like
Jatropha curcas, constituting 40-50% bio-crude oil indicates its
potential as one of the most promising alternatives to conventional
sources of energy. Also, limited studies on utilization of de-oiled cake
have revealed that Jatropha bio-waste has good potential to be used as
organic fertilizers produced via aerobic and anaerobic treatment.
However, their commercial exploitation has not yet been possible. The
present study aims at developing appropriate bio-processes and
formulations utilizing Jatropha seed cake as organic fertilizer, for
improving the growth of Polianthes tuberose L. (Tuberose). Pot
experiments were carried out by growing tuberose plants on soil
treated with composted formulations of Jatropha de-oiled cake, Farm
Yard Manure (FYM) and inorganic fertilizers were also blended in
soil. The treatment was carried out through soil amendment as well as
foliar spray. The growth and morphological parameters were
monitored for entire crop cycle.
The growth Length and number of leaves, spike length, rachis
length, number of bulb per plant and earliness of sprouting of bulb and
yield enhancement were comparable to that achieved under inorganic
fertilizer. Furthermore, performance of inorganic fertilizer also showed
an improvement when blended with composted bio-waste. These
findings would open new avenues for Jatropha based bio-wastes to be
composted and used as organic fertilizers for commercial floriculture.
Abstract: Cosmic showers, from their places of origin in space,
after entering earth generate secondary particles called Extensive Air
Shower (EAS). Detection and analysis of EAS and similar High
Energy Particle Showers involve a plethora of experimental setups
with certain constraints for which soft-computational tools like
Artificial Neural Network (ANN)s can be adopted. The optimality
of ANN classifiers can be enhanced further by the use of Multiple
Classifier System (MCS) and certain data - dimension reduction
techniques. This work describes the performance of certain data
dimension reduction techniques like Principal Component Analysis
(PCA), Independent Component Analysis (ICA) and Self Organizing
Map (SOM) approximators for application with an MCS formed
using Multi Layer Perceptron (MLP), Recurrent Neural Network
(RNN) and Probabilistic Neural Network (PNN). The data inputs are
obtained from an array of detectors placed in a circular arrangement
resembling a practical detector grid which have a higher dimension
and greater correlation among themselves. The PCA, ICA and SOM
blocks reduce the correlation and generate a form suitable for real
time practical applications for prediction of primary energy and
location of EAS from density values captured using detectors in a
circular grid.
Abstract: Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.
Abstract: The fixed partial dentures are mainly used in the frontal
part of the dental arch because of their great esthetics. There are
several factors that are associated with the stress state created in
ceramic restorations, including: thickness of ceramic layers,
mechanical properties of the materials, elastic modulus of the
supporting substrate material, direction, magnitude and frequency of
applied load, size and location of occlusal contact areas, residual
stresses induced by processing or pores, restoration-cement
interfacial defects and environmental defects. The purpose of this
study is to evaluate the capability of Polarization Sensitive Optical
Coherence Tomography (PSOCT) in detection and analysis of
possible material defects in metal-ceramic and integral ceramic fixed
partial dentures. As a conclusion, it is important to have a non
invasive method to investigate fixed partial prostheses before their
insertion in the oral cavity in order to satisfy the high stress
requirements and the esthetic function.
Abstract: Discrimination between different classes of environmental
sounds is the goal of our work. The use of a sound recognition
system can offer concrete potentialities for surveillance and
security applications. The first paper contribution to this research
field is represented by a thorough investigation of the applicability
of state-of-the-art audio features in the domain of environmental
sound recognition. Additionally, a set of novel features obtained by
combining the basic parameters is introduced. The quality of the
features investigated is evaluated by a HMM-based classifier to which
a great interest was done. In fact, we propose to use a Multi-Style
training system based on HMMs: one recognizer is trained on a
database including different levels of background noises and is used
as a universal recognizer for every environment. In order to enhance
the system robustness by reducing the environmental variability, we
explore different adaptation algorithms including Maximum Likelihood
Linear Regression (MLLR), Maximum A Posteriori (MAP)
and the MAP/MLLR algorithm that combines MAP and MLLR.
Experimental evaluation shows that a rather good recognition rate
can be reached, even under important noise degradation conditions
when the system is fed by the convenient set of features.
Abstract: Both the minimum energy consumption and
smoothness, which is quantified as a function of jerk, are generally
needed in many dynamic systems such as the automobile and the
pick-and-place robot manipulator that handles fragile equipments.
Nevertheless, many researchers come up with either solely
concerning on the minimum energy consumption or minimum jerk
trajectory. This research paper proposes a simple yet very interesting
relationship between the minimum direct and indirect jerks
approaches in designing the time-dependent system yielding an
alternative optimal solution. Extremal solutions for the cost functions
of direct and indirect jerks are found using the dynamic optimization
methods together with the numerical approximation. This is to allow
us to simulate and compare visually and statistically the time history
of control inputs employed by minimum direct and indirect jerk
designs. By considering minimum indirect jerk problem, the
numerical solution becomes much easier and yields to the similar
results as minimum direct jerk problem.
Abstract: One of the robust fault detection filter (RFDF)
designing method is based on sliding-mode theory. The main purpose
of our study is to introduce an innovative simplified reference
residual model generator to formulate the RFDF as a sliding-mode
observer without any manipulation package or transformation matrix,
through which the generated residual signals can be evaluated. So the
proposed design is more explicit and requires less design parameters
in comparison with approaches requiring changing coordinates. To
the best author's knowledge, this is the first time that the sliding
mode technique is applied to detect actuator and sensor faults in a
real boiler. The designing procedure is proposed in a drum boiler in
Synvendska Kraft AB Plant in Malmo, Sweden as a multivariable
and strongly coupled system. It is demonstrated that both sensor and
actuator faults can robustly be detected. Also sensor faults can be
diagnosed and isolated through this method.
Abstract: In recent years, fast neural networks for object/face detection have been introduced based on cross correlation in the frequency domain between the input matrix and the hidden weights of neural networks. In our previous papers [3,4], fast neural networks for certain code detection was introduced. It was proved in [10] that for fast neural networks to give the same correct results as conventional neural networks, both the weights of neural networks and the input matrix must be symmetric. This condition made those fast neural networks slower than conventional neural networks. Another symmetric form for the input matrix was introduced in [1-9] to speed up the operation of these fast neural networks. Here, corrections for the cross correlation equations (given in [13,15,16]) to compensate for the symmetry condition are presented. After these corrections, it is proved mathematically that the number of computation steps required for fast neural networks is less than that needed by classical neural networks. Furthermore, there is no need for converting the input data into symmetric form. Moreover, such new idea is applied to increase the speed of neural networks in case of processing complex values. Simulation results after these corrections using MATLAB confirm the theoretical computations.
Abstract: In this paper, an analytical approach is used to study the coupled lateral-torsional vibrations of laminated composite beam. It is known that in such structures due to the fibers orientation in various layers, any lateral displacement will produce a twisting moment. This phenomenon is modeled by the bending-twisting material coupling rigidity and its main feature is the coupling of lateral and torsional vibrations. In addition to the material coupling, the effects of shear deformation and rotary inertia are taken into account in the definition of the potential and kinetic energies. Then, the governing differential equations are derived using the Hamilton-s principle and the mathematical model matches the Timoshenko beam model when neglecting the effect of bending-twisting rigidity. The equations of motion which form a system of three coupled PDEs are solved analytically to study the free vibrations of the beam in lateral and rotational modes due to the bending, as well as the torsional mode caused by twisting. The analytic solution is carried out in three steps: 1) assuming synchronous motion for the kinematic variables which are the lateral, rotational and torsional displacements, 2) solving the ensuing eigenvalue problem which contains three coupled second order ODEs and 3) imposing different boundary conditions related to combinations of simply, clamped and free end conditions. The resulting natural frequencies and mode shapes are compared with similar results in the literature and good agreement is achieved.
Abstract: In this paper, we present a maintenance model of a
two-unit series system with economic dependence. Unit#1 which is
considered to be more expensive and more important, is subject to
condition monitoring (CM) at equidistant, discrete time epochs and
unit#2, which is not subject to CM has a general lifetime distribution.
The multivariate observation vectors obtained through condition
monitoring carry partial information about the hidden state of unit#1,
which can be in a healthy or a warning state while operating. Only the
failure state is assumed to be observable for both units. The objective
is to find an optimal opportunistic maintenance policy minimizing
the long-run expected average cost per unit time. The problem
is formulated and solved in the partially observable semi-Markov
decision process framework. An effective computational algorithm
for finding the optimal policy and the minimum average cost is
developed, illustrated by a numerical example.
Abstract: Mobile ad-hoc networks (MANETs) are a form of
wireless networks which do not require a base station for providing
network connectivity. Mobile ad-hoc networks have many
characteristics which distinguish them from other wireless networks
which make routing in such networks a challenging task. Cluster
based routing is one of the routing schemes for MANETs in which
various clusters of mobile nodes are formed with each cluster having
its own clusterhead which is responsible for routing among clusters.
In this paper we have proposed and implemented a distributed
weighted clustering algorithm for MANETs. This approach is based
on combined weight metric that takes into account several system
parameters like the node degree, transmission range, energy and
mobility of the nodes. We have evaluated the performance of
proposed scheme through simulation in various network situations.
Simulation results show that proposed scheme outperforms the
original distributed weighted clustering algorithm (DWCA).