Abstract: Response surface methodology (RSM) is a very
efficient tool to provide a good practical insight into developing new
process and optimizing them. This methodology could help
engineers to raise a mathematical model to represent the behavior of
system as a convincing function of process parameters.
Through this paper the sequential nature of the RSM surveyed for process
engineers and its relationship to design of experiments (DOE), regression
analysis and robust design reviewed. The proposed four-step procedure in
two different phases could help system analyst to resolve the parameter
design problem involving responses. In order to check accuracy of the
designed model, residual analysis and prediction error sum of squares
(PRESS) described.
It is believed that the proposed procedure in this study can resolve a
complex parameter design problem with one or more responses. It can be
applied to those areas where there are large data sets and a number of
responses are to be optimized simultaneously. In addition, the proposed
procedure is relatively simple and can be implemented easily by using
ready-made standard statistical packages.
Abstract: Oxygen transfer, the process by which oxygen is
transferred from the gaseous to liquid phase, is a vital part of the
waste water treatment process. Because of low solubility of
oxygen and consequent low rate of oxygen transfer, sufficient
oxygen to meet the requirement of aerobic waste does not enter
through normal surface air water interface. Many theories have
come up in explaining the mechanism of gas transfer and
absorption of non-reacting gases in a liquid, of out of which, Two
film theory is important. An exiting mathematical model
determines approximate value of Overall Gas Transfer coefficient.
The Overall Gas Transfer coefficient, in case of Penetration theory,
is 1.13 time more than that obtained in case of Two film theory.
The difference is due to the difference in assumptions in the two
theories.
The paper aims at development of mathematical model which
determines the value of Overall Gas Transfer coefficient with
greater accuracy than the existing model.
Abstract: The excellent suitability of the externally excited synchronous
machine (EESM) in automotive traction drive applications
is justified by its high efficiency over the whole operation range and
the high availability of materials. Usually, maximum efficiency is
obtained by modelling each single loss and minimizing the sum of all
losses. As a result, the quality of the optimization highly depends on
the precision of the model. Moreover, it requires accurate knowledge
of the saturation dependent machine inductances. Therefore, the
present contribution proposes a method to minimize the overall losses
of a salient pole EESM and its inverter in steady state operation based
on measurement data only. Since this method does not require any
manufacturer data, it is well suited for an automated measurement
data evaluation and inverter parametrization. The field oriented control
(FOC) of an EESM provides three current components resp. three
degrees of freedom (DOF). An analytic minimization of the copper
losses in the stator and the rotor (assuming constant inductances) is
performed and serves as a first approximation of how to choose the
optimal current reference values. After a numeric offline minimization
of the overall losses based on measurement data the results are
compared to a control strategy that satisfies cos (ϕ) = 1.
Abstract: This paper examines the concept of simulation from
a modelling viewpoint. How can one Mealy machine simulate the other one? We create formalism for simulation of Mealy machines.
The injective s–morphism of the machine semigroups induces the simulation of machines [1]. We present the example of s–morphism
such that it is not a homomorphism of semigroups. The story for the
surjective s–morphisms is quite different. These are homomorphisms
of semigroups but there exists the surjective s–morphism such that it does not induce the simulation.
Abstract: Background noise is particularly damaging to speech
intelligibility for people with hearing loss especially for sensorineural
loss patients. Several investigations on speech intelligibility have
demonstrated sensorineural loss patients need 5-15 dB higher SNR
than the normal hearing subjects. This paper describes Discrete
Cosine Transform Power Normalized Least Mean Square algorithm
to improve the SNR and to reduce the convergence rate of the LMS
for Sensory neural loss patients. Since it requires only real arithmetic,
it establishes the faster convergence rate as compare to time domain
LMS and also this transformation improves the eigenvalue
distribution of the input autocorrelation matrix of the LMS filter.
The DCT has good ortho-normal, separable, and energy compaction
property. Although the DCT does not separate frequencies, it is a
powerful signal decorrelator. It is a real valued function and thus
can be effectively used in real-time operation. The advantages of
DCT-LMS as compared to standard LMS algorithm are shown via
SNR and eigenvalue ratio computations. . Exploiting the symmetry
of the basis functions, the DCT transform matrix [AN] can be
factored into a series of ±1 butterflies and rotation angles. This
factorization results in one of the fastest DCT implementation. There
are different ways to obtain factorizations. This work uses the fast
factored DCT algorithm developed by Chen and company. The
computer simulations results show superior convergence
characteristics of the proposed algorithm by improving the SNR at
least 10 dB for input SNR less than and equal to 0 dB, faster
convergence speed and better time and frequency characteristics.
Abstract: This study presents a hybrid neural network and Gravitational Search Algorithm (HNGSA) method to solve well known Wessinger's equation. To aim this purpose, gravitational search algorithm (GSA) technique is applied to train a multi-layer perceptron neural network, which is used as approximation solution of the Wessinger's equation. A trial solution of the differential equation is written as sum of two parts. The first part satisfies the initial/ boundary conditions and does not contain any adjustable parameters and the second part which is constructed so as not to affect the initial/boundary conditions. The second part involves adjustable parameters (the weights and biases) for a multi-layer perceptron neural network. In order to demonstrate the presented method, the obtained results of the proposed method are compared with some known numerical methods. The given results show that presented method can introduce a closer form to the analytic solution than other numerical methods. Present method can be easily extended to solve a wide range of problems.
Abstract: This paper evaluates the association between
economic environment in the districts of Madrid (Spain) and physical
inactivity, using income per capita as indicator of economic
environment. The analysis included 6,601 individuals aged 16 to 74
years. The measure of association estimated was the prevalence odds
ratio for physical inactivity by income per capita. After adjusting for
sex, age, and individual socioeconomic characteristics, people living
in the districts with the lowest per capita income had an odds ratio for
physical inactivity 1.58 times higher (95% confidence interval 1.35 to
1.85) than those living in districts with the highest per capita income.
Additional adjustment for the availability of sports facilities in each
district did not decrease the magnitude of the association. These
findings show that the widely believed assumption that the
availability of sports and recreational facilities, as a possible
explanation for the relation between economic environment and
physical inactivity, cannot be considered a universal observation.
Abstract: The decisions made by admission control algorithms are
based on the availability of network resources viz. bandwidth, energy,
memory buffers, etc., without degrading the Quality-of-Service (QoS)
requirement of applications that are admitted. In this paper, we
present an energy-aware admission control (EAAC) scheme which
provides admission control for flows in an ad hoc network based
on the knowledge of the present and future residual energy of the
intermediate nodes along the routing path. The aim of EAAC is to
quantify the energy that the new flow will consume so that it can
be decided whether the future residual energy of the nodes along
the routing path can satisfy the energy requirement. In other words,
this energy-aware routing admits a new flow iff any node in the
routing path does not run out of its energy during the transmission
of packets. The future residual energy of a node is predicted using
the Multi-layer Neural Network (MNN) model. Simulation results
shows that the proposed scheme increases the network lifetime. Also
the performance of the MNN model is presented.
Abstract: In recent years, rehabilitation has been the subject of extensive research due to increased spending on building work and repair of built works. In all cases, it is absolutely essential to carry out methods of strengthening or repair of structural elements, and that following an inspection analysis and methodology of a correct diagnosis. The reinforced concrete columns are important elements in building structures. They support the vertical loads and provide bracing against the horizontal loads. This research about the behavior of reinforced concrete rectangular columns, rehabilitated by concrete liner, confinement FRP fabric, steel liner or cage formed by metal corners. It allows comparing the contributions of different processes used perspective section resistance elements rehabilitated compared to that is not reinforced or repaired. The different results obtained revealed a considerable gain in bearing capacity failure of reinforced sections cladding concrete, metal bracket, steel plates and a slight improvement to the section reinforced with fabric FRP. The use of FRP does not affect the weight of the structures, but the use of different techniques cladding increases the weight of elements rehabilitated and therefore the weight of the building which requires resizing foundations.
Abstract: We present a method to create special domain
collections from news sites. The method only requires a single
sample article as a seed. No prior corpus statistics are needed and the
method is applicable to multiple languages. We examine various
similarity measures and the creation of document collections for
English and Japanese. The main contributions are as follows. First,
the algorithm can build special domain collections from as little as
one sample document. Second, unlike other algorithms it does not
require a second “general" corpus to compute statistics. Third, in our
testing the algorithm outperformed others in creating collections
made up of highly relevant articles.
Abstract: Morgan-s refinement calculus (MRC) is one of the
well-known methods allowing the formality presented in the program
specification to be continued all the way to code. On the other hand,
Object-Z (OZ) is an extension of Z adding support for classes and
objects. There are a number of methods for obtaining code from OZ
specifications that can be categorized into refinement and animation
methods. As far as we know, only one refinement method exists
which refines OZ specifications into code. However, this method
does not have fine-grained refinement rules and thus cannot be
automated. On the other hand, existing animation methods do not
present mapping rules formally and do not support the mapping of
several important constructs of OZ, such as all cases of operation
expressions and most of constructs in global paragraph. In this paper,
with the aim of providing an automatic path from OZ specifications
to code, we propose an approach to map OZ specifications into their
counterparts in MRC in order to use fine-grained refinement rules of
MRC. In this way, having counterparts of our specifications in MRC,
we can refine them into code automatically using MRC tools such as
RED. Other advantages of our work pertain to proposing mapping
rules formally, supporting the mapping of all important constructs of
Object-Z, and considering dynamic instantiation of objects while OZ
itself does not cover this facility.
Abstract: In this paper we propose a new criterion for solving
the problem of channel shortening in multi-carrier systems. In a
discrete multitone receiver, a time-domain equalizer (TEQ) reduces
intersymbol interference (ISI) by shortening the effective duration of
the channel impulse response. Minimum mean square error (MMSE)
method for TEQ does not give satisfactory results. In [1] a new
criterion for partially equalizing severe ISI channels to reduce the
cyclic prefix overhead of the discrete multitone transceiver (DMT),
assuming a fixed transmission bandwidth, is introduced. Due to
specific constrained (unit morm constraint on the target impulse
response (TIR)) in their method, the freedom to choose optimum
vector (TIR) is reduced. Better results can be obtained by avoiding
the unit norm constraint on the target impulse response (TIR). In
this paper we change the cost function proposed in [1] to the cost
function of determining the maximum of a determinant subject to
linear matrix inequality (LMI) and quadratic constraint and solve the
resulting optimization problem. Usefulness of the proposed method
is shown with the help of simulations.
Abstract: Carboneous catalytical methane decomposition is an
attractive process because it produces two valuable products:
hydrogen and carbon. Furthermore, this reaction does not emit any
green house or hazardous gases. In the present study, experiments
were conducted in a thermo gravimetric analyzer using Fluka 05120
as carboneous catalyst to analyze its effectiveness in methane
decomposition. Various temperatures and methane partial pressures
were chosen and carbon mass gain was observed as a function of
time. Results are presented in terms of carbon formation rate,
hydrogen production and catalytical activity. It is observed that there
is linearity in carbon deposition amount by time at lower reaction
temperature (780 °C). On the other hand, it is observed that carbon
and hydrogen formation rates are increased with increasing
temperature. Finally, we observed that the carbon formation rate is
highest at 950 °C within the range of temperatures studied.
Abstract: This work deals with modeling and simulation of SO2 removal in a ceramic membrane by means of FEM. A mass transfer model was developed to predict the performance of SO2 absorption in a chemical solvent. The model was based on solving conservation equations for gas component in the membrane. Computational fluid dynamics (CFD) of mass and momentum were used to solve the model equations. The simulations aimed to obtain the distribution of gas concentration in the absorption process. The effect of the operating parameters on the efficiency of the ceramic membrane was evaluated. The modeling findings showed that the gas phase velocity has significant effect on the removal of gas whereas the liquid phase does not affect the SO2 removal significantly. It is also indicated that the main mass transfer resistance is placed in the membrane and gas phase because of high tortuosity of the ceramic membrane.
Abstract: Hydrogen is an important chemical in many industries
and it is expected to become one of the major fuels for energy
generation in the future. Unfortunately, hydrogen does not exist in its
elemental form in nature and therefore has to be produced from
hydrocarbons, hydrogen-containing compounds or water.
Above its critical point (374.8oC and 22.1MPa), water has lower
density and viscosity, and a higher heat capacity than those of
ambient water. Mass transfer in supercritical water (SCW) is
enhanced due to its increased diffusivity and transport ability. The
reduced dielectric constant makes supercritical water a better solvent
for organic compounds and gases. Hence, due to the aforementioned
desirable properties, there is a growing interest toward studies
regarding the gasification of organic matter containing biomass or
model biomass solutions in supercritical water.
In this study, hydrogen and biofuel production by the catalytic
gasification of 2-Propanol in supercritical conditions of water was
investigated. Pt/Al2O3and Ni/Al2O3were the catalysts used in the
gasification reactions. All of the experiments were performed under a
constant pressure of 25MPa. The effects of five reaction temperatures
(400, 450, 500, 550 and 600°C) and five reaction times (10, 15, 20,
25 and 30 s) on the gasification yield and flammable component
content were investigated.
Abstract: Quality of Service (QoS) Routing aims to find path between source and destination satisfying the QoS requirements which efficiently using the network resources and underlying routing algorithm and to fmd low-cost paths that satisfy given QoS constraints. One of the key issues in providing end-to-end QoS guarantees in packet networks is determining feasible path that satisfies a number of QoS constraints. We present a Optimized Multi- Constrained Routing (OMCR) algorithm for the computation of constrained paths for QoS routing in computer networks. OMCR applies distance vector to construct a shortest path for each destination with reference to a given optimization metric, from which a set of feasible paths are derived at each node. OMCR is able to fmd feasible paths as well as optimize the utilization of network resources. OMCR operates with the hop-by-hop, connectionless routing model in IP Internet and does not create any loops while fmding the feasible paths. Nodes running OMCR not necessarily maintaining global view of network state such as topology, resource information and routing updates are sent only to neighboring nodes whereas its counterpart link-state routing method depend on complete network state for constrained path computation and that incurs excessive communication overhead.
Abstract: This paper presents a new classification algorithm using colour and texture for obstacle detection. Colour information is computationally cheap to learn and process. However in many cases, colour alone does not provide enough information for classification. Texture information can improve classification performance but usually comes at an expensive cost. Our algorithm uses both colour and texture features but texture is only needed when colour is unreliable. During the training stage, texture features are learned specifically to improve the performance of a colour classifier. The algorithm learns a set of simple texture features and only the most effective features are used in the classification stage. Therefore our algorithm has a very good classification rate while is still fast enough to run on a limited computer platform. The proposed algorithm was tested with a challenging outdoor image set. Test result shows the algorithm achieves a much better trade-off between classification performance and efficiency than a typical colour classifier.
Abstract: Mobile Ad hoc network consists of a set of mobile
nodes. It is a dynamic network which does not have fixed topology.
This network does not have any infrastructure or central
administration, hence it is called infrastructure-less network. The
change in topology makes the route from source to destination as
dynamic fixed and changes with respect to time. The nature of
network requires the algorithm to perform route discovery, maintain
route and detect failure along the path between two nodes [1]. This
paper presents the enhancements of ARA [2] to improve the
performance of routing algorithm. ARA [2] finds route between
nodes in mobile ad-hoc network. The algorithm is on-demand source
initiated routing algorithm. This is based on the principles of swarm
intelligence. The algorithm is adaptive, scalable and favors load
balancing. The improvements suggested in this paper are handling of
loss ants and resource reservation.
Abstract: With the development of the Polyvinyl chloride
(PVC) products in many applications, the challenge of investigating
the raw material composition and reducing the cost have both
become more and more important. Considerable research has been
done investigating the effect of additives on the PVC products. Most
of the PVC composites research investigates only the effect of
single/few factors, at a time. This isolated consideration of the input
factors does not take in consideration the interaction effect of the
different factors. This paper implements a mixture experimental
design approach to find out a cost-effective PVC composition for the
production of electrical-insulation cables considering the ASTM
Designation (D) 6096. The results analysis showed that a minimum
cost can be achieved through using 20% virgin PVC, 18.75%
recycled PVC, 43.75% CaCO3 with participle size 10 microns, 14%
DOP plasticizer, and 3.5% CPW plasticizer. For maximum UTS the
compound should consist of: 17.5% DOP, 62.5% virgin PVC, and
20.0% CaCO3 of particle size 5 microns. Finally, for the highest
ductility the compound should be made of 35% virgin PVC, 20%
CaCO3 of particle size 5 microns, and 45.0% DOP plasticizer.
Abstract: Multilobe bearings are found to be more stable than circular bearings. A three lobe bearing also possesses good stability characteristics. Sometimes the line of action of the load does not pass through the axis of a bearing and is shifted on either side by a few degrees. Load orientation is one of the factors that affect the stability of a three lobe bearing. The effect of load orientation on the stability of a three-lobe has been discussed in this paper. The results show that stability of a three-lobe bearing supporting either rigid or flexible rotor is increased for the positive values of load orientation i.e. when the load line is shifted in the opposite direction of rotation.