Abstract: The effect of different combinations of response
feedback on the performance of active control system on nonlinear
frames has been studied in this paper. To this end different feedback
combinations including displacement, velocity, acceleration and full
response feedback have been utilized in controlling the response of
an eight story bilinear hysteretic frame which has been subjected to a
white noise excitation and controlled by eight actuators which could
fully control the frame. For active control of nonlinear frame
Newmark nonlinear instantaneous optimal control algorithm has been
used which a diagonal matrix has been selected for weighting
matrices in performance index. For optimal design of active control
system while the objective has been to reduce the maximum drift to
below the yielding level, Distributed Genetic Algorithm (DGA) has
been used to determine the proper set of weighting matrices. The
criteria to assess the effect of each combination of response feedback
have been the minimum required control force to reduce the
maximum drift to below the yielding drift. The results of numerical
simulation show that the performance of active control system is
dependent on the type of response feedback where the velocity
feedback is more effective in designing optimal control system in
comparison with displacement and acceleration feedback. Also using
full feedback of response in controller design leads to minimum
control force amongst other combinations. Also the distributed
genetic algorithm shows acceptable convergence speed in solving the
optimization problem of designing active control systems.
Abstract: The present work is a numerical simulation of
nanofluids flow in a double pipe heat exchanger provided with
porous baffles. The hot nanofluid flows in the inner cylinder, whereas
the cold nanofluid circulates in the annular gap. The Darcy-
Brinkman-Forchheimer model is adopted to describe the flow in the
porous regions, and the governing equations with the appropriate
boundary conditions are solved by the finite volume method. The
results reveal that the addition of metallic nanoparticles enhances the
rate of heat transfer in comparison to conventional fluids but this
augmentation is accompanied by an increase in pressure drop. The
highest heat exchanger performances are obtained when
nanoparticles are added only to the cold fluid.
Abstract: In this paper, the construction of fast algorithms for the computation of Periodic Walsh Piecewise-Linear PWL transform and the Periodic Haar Piecewise-Linear PHL transform will be presented. Algorithms for the computation of the inverse transforms are also proposed. The matrix equation of the PWL and PHL transforms are introduced. Comparison of the computational requirements for the periodic piecewise-linear transforms and other orthogonal transforms shows that the periodic piecewise-linear transforms require less number of operations than some orthogonal transforms such as the Fourier, Walsh and the Discrete Cosine transforms.
Abstract: An automated wood recognition system is designed to
classify tropical wood species.The wood features are extracted based
on two feature extractors: Basic Grey Level Aura Matrix (BGLAM)
technique and statistical properties of pores distribution (SPPD)
technique. Due to the nonlinearity of the tropical wood species
separation boundaries, a pre classification stage is proposed which
consists ofKmeans clusteringand kernel discriminant analysis (KDA).
Finally, Linear Discriminant Analysis (LDA) classifier and KNearest
Neighbour (KNN) are implemented for comparison purposes.
The study involves comparison of the system with and without pre
classification using KNN classifier and LDA classifier.The results
show that the inclusion of the pre classification stage has improved
the accuracy of both the LDA and KNN classifiers by more than
12%.
Abstract: Surgical site infections (SSIs) are the most common
nosocomial infection in surgical patients resulting in significant
increases in postoperative morbidity and mortality. The commonly
causative bacteria developed resistance to virtually all antibiotics
available. The aim of this study was to isolation and identification the
most common bacteria that cause SSIs in Medical Research Institute,
and to compare their sensitivity to selected group of antibiotics and
natural products (garlic, oregano, olive, and Nigella sativa oils). The
isolated pathogens collected from infected surgical wounds were
identified, and their sensitivities to the antibiotics commonly
available for clinical use, and also to the different concentrations of
the used natural products were investigated. The results indicate to
the potential therapeutic effect of the tested natural products in
treatment of surgical wound infections.
Abstract: In this project cadmium ions were adsorbed from
aqueous solutions onto either date pits; a cheap agricultural and nontoxic
material, or chemically activated carbon prepared from date pits
using phosphoric acid. A series of experiments were conducted in a
batch adsorption technique to assess the feasibility of using the
prepared adsorbents. The effects of the process variables such as
initial cadmium ions concentration, contact time, solution pH and
adsorbent dose on the adsorption capacity of both adsorbents were
studied. The experimental data were tested using different isotherm
models such as Langmuir, Freundlich, Tempkin and Dubinin-
Radushkevich. The results showed that although the equilibrium data
could be described by all models used, Langmuir model gave slightly
better results when using activated carbon while Freundlich model,
gave better results with date pits.
Abstract: Whilst there is growing evidence that activity across
the lifespan is beneficial for improved health, there are also many
changes involved with the aging process and subsequently the
potential for reduced indices of health. The nexus between all forms
of health, physical activity and aging is complex and has raised much
interest in recent times due to the realization that a multifaceted
approached is necessary in order to counteract a growing obesity
epidemic. By investigating age based trends within a population
adherring to competitive sport at older ages, further insight might be
gleaned to assist in understanding one of many factors influencing
this relationship. This study evaluated those sport psychological
constructs of health, physical fitness, mental health states, and social
dimension factors in sport that were associated with factors to
participate in sport and physical activity based on responses from the
2009 World Masters Games in Sydney. The sample consisted of
7846 athletes who competed at the games and who completed a 56
item sports participation survey using a 7-point Likert response (1 -
not important to 7 - very important). Questions focuses on factors
thought to promote participation, such as weight control, living
longer, improving mental health (self-esteem, mood states),
improving physical health and factors related to the athlete-s
competitive perspective. The most significant factors related to
participation with this cohort of masters athletes were the socializing
environment of sport, getting physically fit and improving
competitive personal best performances. Strategies to increase
participation in masters sport should focus on these factors as other
factors such as weight loss, improving mental health and living
longer were not identified as important determinates of sports
participation at the World Masters level.
Abstract: Today air-core coils (ACC) are a viable alternative to
ferrite-core coils in a range of applications due to their low induction
effect. An analytical study was carried out and the results were used as
a guide to understand the relationship between the magnet-coil
distance and the resulting attractive magnetic force. Four different
ACC models were fabricated for experimental study. The variation in
the models included the dimensions, the number of coil turns and the
current supply to the coil. Comparison between the analytical and
experimental results for all the models shows an average discrepancy
of less than 10%. An optimized ACC design was selected for the
scanner which can provide maximum magnetic force.
Abstract: This paper describes a new method for affine parameter
estimation between image sequences. Usually, the parameter
estimation techniques can be done by least squares in a quadratic
way. However, this technique can be sensitive to the presence
of outliers. Therefore, parameter estimation techniques for various
image processing applications are robust enough to withstand the
influence of outliers. Progressively, some robust estimation functions
demanding non-quadratic and perhaps non-convex potentials adopted
from statistics literature have been used for solving these. Addressing
the optimization of the error function in a factual framework for
finding a global optimal solution, the minimization can begin with
the convex estimator at the coarser level and gradually introduce nonconvexity
i.e., from soft to hard redescending non-convex estimators
when the iteration reaches finer level of multiresolution pyramid.
Comparison has been made to find the performance of the results
of proposed method with the results found individually using two
different estimators.
Abstract: This paper presents a comparison of average outgoing
quality limit of the MCSP-2-C plan with MCSP-C when MCSP-2-C
has been developed from MCSP-C. The parameters used in MCSP-2-
C are: i (the clearance number), c (the acceptance number), m (the
number of conforming units to be found before allowing c nonconforming
units in the sampling inspection), f1 and f2 (the sampling
frequency at level 1 and 2, respectively). The average outgoing
quality limit (AOQL) values from two plans were compared and we
found that for all sets of i, r, and c values, MCSP-2-C gives higher
values than MCSP-C. For all sets of i, r, and c values, the average
outgoing quality values of MCSP-C and MCSP-2-C are similar when
p is low or high but is difference when p is moderate.
Abstract: Nowadays there is a growing interest in biofuel production in most countries because of the increasing concerns about hydrocarbon fuel shortage and global climate changes, also for enhancing agricultural economy and producing local needs for transportation fuel. Ethanol can be produced from biomass by the hydrolysis and sugar fermentation processes. In this study ethanol was produced without using expensive commercial enzymes from sugarcane bagasse. Alkali pretreatment was used to prepare biomass before enzymatic hydrolysis. The comparison between NaOH, KOH and Ca(OH)2 shows NaOH is more effective on bagasse. The required enzymes for biomass hydrolysis were produced from sugarcane solid state fermentation via two fungi: Trichoderma longibrachiatum and Aspergillus niger. The results show that the produced enzyme solution via A. niger has functioned better than T. longibrachiatum. Ethanol was produced by simultaneous saccharification and fermentation (SSF) with crude enzyme solution from T. longibrachiatum and Saccharomyces cerevisiae yeast. To evaluate this procedure, SSF of pretreated bagasse was also done using Celluclast 1.5L by Novozymes. The yield of ethanol production by commercial enzyme and produced enzyme solution via T. longibrachiatum was 81% and 50% respectively.
Abstract: This paper presents a new strategy of identification
and classification of pathological voices using the hybrid method
based on wavelet transform and neural networks. After speech
acquisition from a patient, the speech signal is analysed in order to
extract the acoustic parameters such as the pitch, the formants, Jitter,
and shimmer. Obtained results will be compared to those normal and
standard values thanks to a programmable database. Sounds are
collected from normal people and patients, and then classified into
two different categories. Speech data base is consists of several
pathological and normal voices collected from the national hospital
“Rabta-Tunis". Speech processing algorithm is conducted in a
supervised mode for discrimination of normal and pathology voices
and then for classification between neural and vocal pathologies
(Parkinson, Alzheimer, laryngeal, dyslexia...). Several simulation
results will be presented in function of the disease and will be
compared with the clinical diagnosis in order to have an objective
evaluation of the developed tool.
Abstract: The objective of this work is to explicit knowledge on the interactions between the chlorophyll-a and nine meroplankton larvae of epibenthonic fauna. The studied case is the Arraial do Cabo upwelling system, Southeastern of Brazil, which provides different environmental conditions. To assess this information a network approach based in probability estimative was used. Comparisons among the generated graphs are made in the light of different water masses, application of Shannon biodiversity index, and the closeness and betweenness centralities measurements. Our results show the main pattern among different water masses and how the core organisms belonging to the network skeleton are correlated to the main environmental variable. We conclude that the approach of complex networks is a promising tool for environmental diagnostic.
Abstract: As the information age matures, major social
infrastructures such as communication, finance, military and energy,
have become ever more dependent on information communication
systems. And since these infrastructures are connected to the Internet,
electronic intrusions such as hacking and viruses have become a new
security threat. Especially, disturbance or neutralization of a major
social infrastructure can result in extensive material damage and social
disorder. To address this issue, many nations around the world are
researching and developing various techniques and information
security policies as a government-wide effort to protect their
infrastructures from newly emerging threats. This paper proposes an
evaluation method for information security levels of CIIP (Critical
Information Infrastructure Protection), which can enhance the security
level of critical information infrastructure by checking the current
security status and establish security measures accordingly to protect
infrastructures effectively.
Abstract: Precise frequency estimation methods for pulseshaped echoes are a prerequisite to determine the relative velocity between sensor and reflector. Signal frequencies are analysed using three different methods: Fourier Transform, Chirp ZTransform and the MUSIC algorithm. Simulations of echoes are performed varying both the noise level and the number of reflecting points. The superposition of echoes with a random initial phase is found to influence the precision of frequency estimation severely for FFT and MUSIC. The standard deviation of the frequency using FFT is larger than for MUSIC. However, MUSIC is more noise-sensitive. The distorting effect of superpositions is less pronounced in experimental data.
Abstract: The paper presents the results of theoretical and
numerical modeling of propagation of shock waves in bubbly liquids
related to nonlinear effects (realistic equation of state, chemical
reactions, two-dimensional effects). On the basis on the Rankine-
Hugoniot equations the problem of determination of parameters of
passing and reflected shock waves in gas-liquid medium for
isothermal, adiabatic and shock compression of the gas component is
solved by using the wide-range equation of state of water in the
analitic form. The phenomenon of shock wave intensification is
investigated in the channel of variable cross section for the
propagation of a shock wave in the liquid filled with bubbles
containing chemically active gases. The results of modeling of the
wave impulse impact on the solid wall covered with bubble layer are
presented.
Abstract: The paper presents a one-dimensional transient
mathematical model of compressible non-isothermal multicomponent
fluid mixture flow in a pipe. The set of the mass,
momentum and enthalpy conservation equations for gas phase is
solved in the model. Thermo-physical properties of multi-component
gas mixture are calculated by solving the Equation of State (EOS)
model. The Soave-Redlich-Kwong (SRK-EOS) model is chosen. Gas
mixture viscosity is calculated on the basis of the Lee-Gonzales-
Eakin (LGE) correlation. Numerical analysis of rapid gas
decompression process in rich and base natural gases is made on the
basis of the proposed mathematical model. The model is successfully
validated on the experimental data [1]. The proposed mathematical
model shows a very good agreement with the experimental data [1] in
a wide range of pressure values and predicts the decompression in
rich and base gas mixtures much better than analytical and
mathematical models, which are available from the open source
literature.
Abstract: Active vibration control is an important problem in
structures. The objective of active vibration control is to reduce the vibrations of a system by automatic modification of the system-s
structural response. In this paper, the modeling and design of a fast
output sampling feedback controller for a smart flexible beam system embedded with shear sensors and actuators for SISO system using
Timoshenko beam theory is proposed. FEM theory, Timoshenko beam theory and the state space techniques are used to model the
aluminum cantilever beam. For the SISO case, the beam is divided into 5 finite elements and the control actuator is placed at finite
element position 1, whereas the sensor is varied from position 2 to 5, i.e., from the nearby fixed end to the free end. Controllers are
designed using FOS method and the performance of the designed FOS controller is evaluated for vibration control for 4 SISO models
of the same plant. The effect of placing the sensor at different locations on the beam is observed and the performance of the
controller is evaluated for vibration control. Some of the limitations of the Euler-Bernoulli theory such as the neglection of shear and
axial displacement are being considered here, thus giving rise to an accurate beam model. Embedded shear sensors and actuators have
been considered in this paper instead of the surface mounted sensors
and actuators for vibration suppression because of lot of advantages. In controlling the vibration modes, the first three dominant modes of
vibration of the system are considered.
Abstract: Principle component analysis is often combined with
the state-of-art classification algorithms to recognize human faces.
However, principle component analysis can only capture these
features contributing to the global characteristics of data because it is a
global feature selection algorithm. It misses those features
contributing to the local characteristics of data because each principal
component only contains some levels of global characteristics of data.
In this study, we present a novel face recognition approach using
non-negative principal component analysis which is added with the
constraint of non-negative to improve data locality and contribute to
elucidating latent data structures. Experiments are performed on the
Cambridge ORL face database. We demonstrate the strong
performances of the algorithm in recognizing human faces in
comparison with PCA and NREMF approaches.
Abstract: The paper discusses the results obtained to predict
reinforcement in singly reinforced beam using Neural Net (NN),
Support Vector Machines (SVM-s) and Tree Based Models. Major
advantage of SVM-s over NN is of minimizing a bound on the
generalization error of model rather than minimizing a bound on
mean square error over the data set as done in NN. Tree Based
approach divides the problem into a small number of sub problems to
reach at a conclusion. Number of data was created for different
parameters of beam to calculate the reinforcement using limit state
method for creation of models and validation. The results from this
study suggest a remarkably good performance of tree based and
SVM-s models. Further, this study found that these two techniques
work well and even better than Neural Network methods. A
comparison of predicted values with actual values suggests a very
good correlation coefficient with all four techniques.