Abstract: Molar excess Volumes, VE ijk and speeds of sound , uijk of 2-pyrrolidinone (i) + benzene or toluene (j) + ethanol (k) ternary mixture have been measured as a function of composition at 308.15 K. The observed speeds of sound data have been utilized to determine excess isentropic compressiblities, ( E S κ )ijk of ternary (i + j + k) mixtures. Molar excess volumes, VE ijk and excess isentropic compressibilities, ( E S κ )ijk data have fitted to the Redlich-Kister equation to calculate ternary adjustable parameters and standard deviations. The Moelywn-Huggins concept (Huggins in Polymer 12: 389-399, 1971) of connectivity between the surfaces of the constituents of binary mixtures has been extended to ternary mixtures (using the concept of a connectivity parameter of third degree of molecules, 3ξ , which inturn depends on its topology) to obtain an expression that describes well the measured VE ijk and ( E S κ )ijk data.
Abstract: In this paper, the criteria of Ψ-eventual stability have been established for generalized impulsive differential systems of multiple dependent variables. The sufficient conditions have been obtained using piecewise continuous Lyapunov function. An example is given to support our theoretical result.
Abstract: In this study concept of experimental design is
successfully applied for the determination of optimum condition to
produce PP/SWCNT (Polypropylene/Single wall carbon nanotube)
nanocomposite. Central composite design as one of experimental
design techniques is employed for the optimization and statistical
determination of the significant factors influencing on the tensile
modulus and yield stress as mechanical properties of this
nanocomposite. The significant factors are SWCNT weight fraction
and acid treatment time for functionalizing the nanoparticles.
Optimum conditions are in 0.7 % of SWCNT weight fraction and 210
min as acid treatment time for 1112.75 ± 28 MPa as maximum tensile
modulus and in 216 min and 0.65 % as acid treatment time and
SWCNT weight fraction respectively for 40.26 ± 0.3 MPa as
maximum yield stress. Also after setting new experiments for test
these optimum conditions, found excelent agreement with predicted
values.
Abstract: Nanostructured materials have attracted many
researchers due to their outstanding mechanical and physical
properties. For example, carbon nanotubes (CNTs) or carbon
nanofibres (CNFs) are considered to be attractive reinforcement
materials for light weight and high strength metal matrix composites.
These composites are being projected for use in structural
applications for their high specific strength as well as functional
materials for their exciting thermal and electrical characteristics. The
critical issues of CNT-reinforced MMCs include processing
techniques, nanotube dispersion, interface, strengthening mechanisms
and mechanical properties. One of the major obstacles to the effective
use of carbon nanotubes as reinforcements in metal matrix
composites is their agglomeration and poor distribution/dispersion
within the metallic matrix. In order to tap into the advantages of the
properties of CNTs (or CNFs) in composites, the high dispersion of
CNTs (or CNFs) and strong interfacial bonding are the key issues
which are still challenging. Processing techniques used for synthesis
of the composites have been studied with an objective to achieve
homogeneous distribution of carbon nanotubes in the matrix.
Modified mechanical alloying (ball milling) techniques have emerged
as promising routes for the fabrication of carbon nanotube (CNT)
reinforced metal matrix composites. In order to obtain a
homogeneous product, good control of the milling process, in
particular control of the ball movement, is essential. The control of
the ball motion during the milling leads to a reduction in grinding
energy and a more homogeneous product. Also, the critical inner
diameter of the milling container at a particular rotational speed can
be calculated. In the present work, we use conventional and modified
mechanical alloying to generate a homogenous distribution of 2 wt.
% CNT within Al powders. 99% purity Aluminium powder (Acros,
200mesh) was used along with two different types of multiwall
carbon nanotube (MWCNTs) having different aspect ratios to
produce Al-CNT composites. The composite powders were processed
into bulk material by compaction, and sintering using a cylindrical
compaction and tube furnace. Field Emission Scanning electron
microscopy (FESEM), X-Ray diffraction (XRD), Raman
spectroscopy and Vickers macro hardness tester were used to
evaluate CNT dispersion, powder morphology, CNT damage, phase
analysis, mechanical properties and crystal size determination.
Despite the success of ball milling in dispersing CNTs in Al powder,
it is often accompanied with considerable strain hardening of the Al
powder, which may have implications on the final properties of the
composite. The results show that particle size and morphology vary
with milling time. Also, by using the mixing process and sonication
before mechanical alloying and modified ball mill, dispersion of the
CNTs in Al matrix improves.
Abstract: A thin layer on the component surface can be found
with high tensile residual stresses, due to turning operations, which
can dangerously affect the fatigue performance of the component. In
this paper an analytical approach is presented to reconstruct the
residual stress field from a limited incomplete set of measurements.
Airy stress function is used as the primary unknown to directly solve
the equilibrium equations and satisfying the boundary conditions. In
this new method there exists the flexibility to impose the physical
conditions that govern the behavior of residual stress to achieve a
meaningful complete stress field. The analysis is also coupled to a
least squares approximation and a regularization method to provide
stability of the inverse problem. The power of this new method is
then demonstrated by analyzing some experimental measurements
and achieving a good agreement between the model prediction and
the results obtained from residual stress measurement.
Abstract: The Integrated Management of Child illnesses (IMCI) and the surveillance Health Information Systems (HIS) are related strategies that are designed to manage child illnesses and community practices of diseases. However, both strategies do not function well together because of classification incompatibilities and, as such, are difficult to use by health care personnel in rural areas where a majority of people lack the basic knowledge of interpreting disease classification from these methods. This paper discusses a single approach on how a stand-alone expert system can be used as a prompt diagnostic tool for all cases of illnesses presented. The system combines the action-oriented IMCI and the disease-oriented HIS approaches to diagnose malaria and typhoid fever in the rural areas of the Niger-delta region.
Abstract: This paper introduces a novel approach to estimate the
clique potentials of Gibbs Markov random field (GMRF) models
using the Support Vector Machines (SVM) algorithm and the Mean
Field (MF) theory. The proposed approach is based on modeling the
potential function associated with each clique shape of the GMRF
model as a Gaussian-shaped kernel. In turn, the energy function of
the GMRF will be in the form of a weighted sum of Gaussian
kernels. This formulation of the GMRF model urges the use of the
SVM with the Mean Field theory applied for its learning for
estimating the energy function. The approach has been tested on
synthetic texture images and is shown to provide satisfactory results
in retrieving the synthesizing parameters.
Abstract: Wireless Sensor Networks (WSN) are emerging
because of the developments in wireless communication technology and miniaturization of the hardware. WSN consists of a large number of low-cost, low-power, multifunctional sensor nodes to monitor physical conditions, such as temperature, sound, vibration, pressure,
motion, etc. The MAC protocol to be used in the sensor networks must be energy efficient and this should aim at conserving the energy during its operation. In this paper, with the focus of analyzing the
MAC protocols used in wireless Adhoc networks to WSN, simulation
experiments were conducted in Global Mobile Simulator
(GloMoSim) software. Number of packets sent by regular nodes, and received by sink node in different deployment strategies, total energy
spent, and the network life time have been chosen as the metric for comparison. From the results of simulation, it is evident that the IEEE 802.11 protocol performs better compared to CSMA and MACA protocols.
Abstract: In process control applications, above 90% of the
controllers are of PID type. This paper proposed a robust PI
controller with fractional-order integrator. The PI parameters were
obtained using classical Ziegler-Nichols rules but enhanced with the
application of error filter cascaded to the fractional-order PI. The
controller was applied on steam temperature process that was
described by FOPDT transfer function. The process can be classified
as lag dominating process with very small relative dead-time. The
proposed control scheme was compared with other PI controller
tuned using Ziegler-Nichols and AMIGO rules. Other PI controller
with fractional-order integrator known as F-MIGO was also
considered. All the controllers were subjected to set point change and
load disturbance tests. The performance was measured using Integral
of Squared Error (ISE) and Integral of Control Signal (ICO). The
proposed controller produced best performance for all the tests with
the least ISE index.
Abstract: In this paper, a pipelined version of genetic algorithm,
called PLGA, and a corresponding hardware platform are described.
The basic operations of conventional GA (CGA) are made pipelined
using an appropriate selection scheme. The selection operator, used
here, is stochastic in nature and is called SA-selection. This helps
maintaining the basic generational nature of the proposed pipelined
GA (PLGA). A number of benchmark problems are used to compare
the performances of conventional roulette-wheel selection and the
SA-selection. These include unimodal and multimodal functions with
dimensionality varying from very small to very large. It is seen that
the SA-selection scheme is giving comparable performances with
respect to the classical roulette-wheel selection scheme, for all the
instances, when quality of solutions and rate of convergence are considered.
The speedups obtained by PLGA for different benchmarks
are found to be significant. It is shown that a complete hardware
pipeline can be developed using the proposed scheme, if parallel
evaluation of the fitness expression is possible. In this connection
a low-cost but very fast hardware evaluation unit is described.
Results of simulation experiments show that in a pipelined hardware
environment, PLGA will be much faster than CGA. In terms of
efficiency, PLGA is found to outperform parallel GA (PGA) also.
Abstract: The characterization of κ-carrageenan could provide a
better understanding of its functions in biological, medical and
industrial applications. Chemical and physical analyses of
carrageenan from seaweeds, Euchema cottonii L., were done to offer
information on its properties and the effects of Co-60 γ-irradiation on
its thermochemical characteristics. The structural and morphological
characteristics of κ-carrageenan were determined using scanning
electron microscopy (SEM) while the composition, molecular weight
and thermal properties were determined using attenuated total
reflectance Fourier transform infrared spectroscopy (ATR-FTIR), gel
permeation chromatography (GPC), thermal gravimetric analysis
(TGA) and differential scanning calorimetry (DSC). Further chemical
analysis was done using hydrogen-1 nuclear magnetic resonance (1H
NMR) and functional characteristics in terms of biocompatibility
were evaluated using cytotoxicity test.
Abstract: The numerical analytic continuation of a function f(z) = f(x + iy) on a strip is discussed in this paper. The data are only given approximately on the real axis. The periodicity of given data is assumed. A truncated Fourier spectral method has been introduced to deal with the ill-posedness of the problem. The theoretic results show that the discrepancy principle can work well for this problem. Some numerical results are also given to show the efficiency of the method.
Abstract: This paper describes the design and results of FROID,
an outbound intrusion detection system built with agent technology
and supported by an attacker-centric ontology. The prototype
features a misuse-based detection mechanism that identifies remote
attack tools in execution. Misuse signatures composed of attributes
selected through entropy analysis of outgoing traffic streams and
process runtime data are derived from execution variants of attack
programs. The core of the architecture is a mesh of self-contained
detection cells organized non-hierarchically that group agents in a
functional fashion. The experiments show performance gains when
the ontology is enabled as well as an increase in accuracy achieved
when correlation cells combine detection evidence received from
independent detection cells.
Abstract: This paper presents functionality of negotiation agent
on value-based design decision. The functionality is based on the
characteristics of the system and goal specification. A Prometheus
Design Tool model was used for developing the system. Group
functionality will be the attribute for negotiation agents, which
comprises a coordinator agent and decision- maker agent. The results
of the testing of the system to a building system selection on valuebased
decision environment are also presented.
Abstract: Wavelets have provided the researchers with
significant positive results, by entering the texture defect detection domain. The weak point of wavelets is that they are one-dimensional
by nature so they are not efficient enough to describe and analyze two-dimensional functions. In this paper we present a new method to
detect the defect of texture images by using curvelet transform.
Simulation results of the proposed method on a set of standard
texture images confirm its correctness. Comparing the obtained results indicates the ability of curvelet transform in describing
discontinuity in two-dimensional functions compared to wavelet
transform
Abstract: Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton?s methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.
Abstract: Movable power sources of proton exchange
membrane fuel cells (PEMFC) are the important research done in the
current fuel cells (FC) field. The PEMFC system control influences
the cell performance greatly and it is a control system for industrial
complex problems, due to the imprecision, uncertainty and partial
truth and intrinsic nonlinear characteristics of PEMFCs. In this paper
an adaptive PI control strategy using neural network adaptive Morlet
wavelet for control is proposed. It is based on a single layer feed
forward neural networks with hidden nodes of adaptive morlet
wavelet functions controller and an infinite impulse response (IIR)
recurrent structure. The IIR is combined by cascading to the network
to provide double local structure resulting in improving speed of
learning. The proposed method is applied to a typical 1 KW PEMFC
system and the results show the proposed method has more accuracy
against to MLP (Multi Layer Perceptron) method.
Abstract: One of the most basic functions of control engineers is
tuning of controllers. There are always several process loops in the
plant necessitate of tuning. The auto tuned Proportional Integral
Derivative (PID) Controllers are designed for applications where
large load changes are expected or the need for extreme accuracy and
fast response time exists. The algorithm presented in this paper is
used for the tuning PID controller to obtain its parameters with a
minimum computing complexity. It requires continuous analysis of
variation in few parameters, and let the program to do the plant test
and calculate the controller parameters to adjust and optimize the
variables for the best performance. The algorithm developed needs
less time as compared to a normal step response test for continuous
tuning of the PID through gain scheduling.
Abstract: There exists an injective, information-preserving function
that maps a semantic network (i.e a directed labeled network)
to a directed network (i.e. a directed unlabeled network). The edge
label in the semantic network is represented as a topological feature
of the directed network. Also, there exists an injective function that
maps a directed network to an undirected network (i.e. an undirected
unlabeled network). The edge directionality in the directed network
is represented as a topological feature of the undirected network.
Through function composition, there exists an injective function that
maps a semantic network to an undirected network. Thus, aside from
space constraints, the semantic network construct does not have any
modeling functionality that is not possible with either a directed
or undirected network representation. Two proofs of this idea will
be presented. The first is a proof of the aforementioned function
composition concept. The second is a simpler proof involving an
undirected binary encoding of a semantic network.
Abstract: Group key management is an important functional
building block for any secure multicast architecture.
Thereby, it has been extensively studied in the literature.
In this paper we present relevant group key management
protocols. Then, we compare them against some pertinent
performance criteria.