Abstract: This paper describes the development, modeling, and
testing of skyhook and MiniMax control strategies of semi-active
suspension. The control performances are investigated using
Matlab/Simulink [1], with a two-degree-of-freedom quarter car semiactive
suspension system model. The comparison and evaluation of
control result are made using software-in-the-loop simulation (SILS)
method. This paper also outlines the development of a hardware-inthe-
loop simulation (HILS) system. The simulation results show that
skyhook strategy can significantly reduce the resonant peak of body
and provide improvement in vehicle ride comfort. Otherwise,
MiniMax strategy can be employed to effectively improve drive
safety of vehicle by influencing wheel load. The two strategies can
be switched to control semi-active suspension system to fulfill
different requirement of vehicle in different stages.
Abstract: In this paper, a planar antenna for UWB applications
has been proposed. The antenna consists of a square patch, a partial
ground plane and a slot on the ground plane. The proposed antenna is
easy to be integrated with microwave circuitry for low manufacturing
cost. The flat type antenna has a compact structure and the total size
is 14.5×14.5mm2. The result shows that the impedance bandwidth
(VSWR≤ 2) of the proposed antenna is 12.49 GHz (2.95 to 15.44
GHz), which is equivalent to 135.8%. Details of the proposed
compact planar UWB antenna design is presented and discussed.
Abstract: This paper introduces two decoders for binary linear
codes based on Metaheuristics. The first one uses a genetic algorithm
and the second is based on a combination genetic algorithm with
a feed forward neural network. The decoder based on the genetic
algorithms (DAG) applied to BCH and convolutional codes give good
performances compared to Chase-2 and Viterbi algorithm respectively
and reach the performances of the OSD-3 for some Residue
Quadratic (RQ) codes. This algorithm is less complex for linear
block codes of large block length; furthermore their performances
can be improved by tuning the decoder-s parameters, in particular the
number of individuals by population and the number of generations.
In the second algorithm, the search space, in contrast to DAG which
was limited to the code word space, now covers the whole binary
vector space. It tries to elude a great number of coding operations
by using a neural network. This reduces greatly the complexity of
the decoder while maintaining comparable performances.
Abstract: We apply a particle tracking technique to track the motion of individual pathogenic Leptospira. We observe and capture images of motile Leptospira by means of CCD and darkfield microscope. Image processing, statistical theories and simulations are used for data analysis. Based on trajectory patterns, mean square displacement, and power spectral density characteristics, we found that the motion modes are most likely to be directed motion mode (70%) and the rest are either normal diffusion or unidentified mode. Our findings may support the fact that why leptospires are very well efficient toward targeting internal tissues as a result of increase in virulence factor.
Abstract: A two-dimensional numerical simulation of crossflow
around four cylinders in an in-line rectangular configuration is
studied by using the lattice Boltzmann method (LBM). Special
attention is paid to the effect of the spacing between the cylinders.
The Reynolds number ( Re ) is chosen to be e 100 R = and the
spacing ratio L / D is set at 0.5, 1.5, 2.5, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0
and 10.0. Results show that, as in the case of four cylinders in an inline
rectangular configuration , flow fields show four different
features depending on the spacing (single square cylinder, stable
shielding flow, wiggling shielding flow and a vortex shedding flow)
are observed in this study. The effects of spacing ratio on physical
quantities such as mean drag coefficient, Strouhal number and rootmean-
square value of the drag and lift coefficients are also presented.
There is more than one shedding frequency at small spacing ratios.
The mean drag coefficients for downstream cylinders are less than
that of the single cylinder for all spacing ratios. The present results
using the LBM are compared with some existing experimental data
and numerical studies. The comparison shows that the LBM can
capture the characteristics of the bluff body flow reasonably well and
is a good tool for bluff body flow studies.
Abstract: Developed tool is one of system tools for easier access to various scientific areas and real time interactive learning between
lecturer and for hearing impaired students. There is no demand for the lecturer to know Sign Language (SL). Instead, the new software
tools will perform the translation of the regular speech into SL, after
which it will be transferred to the student. On the other side, the
questions of the student (in SL) will be translated and transferred to
the lecturer in text or speech. One of those tools is presented tool. It-s
too for developing the correct Speech Visemes as a root of total communication method for hearing impared students.
Abstract: It has often been said that the strength of any country
resides in the strength of its industrial sector, and Progress in
industrial society has been accomplished by the creation of new
technologies. Developments have been facilitated by the increasing
availability of advanced manufacturing technology (AMT), in
addition the implementation of advanced manufacturing technology
(AMT) requires careful planning at all levels of the organization to
ensure that the implementation will achieve the intended goals.
Justification and implementation of advanced manufacturing
technology (AMT) involves decisions that are crucial for the
practitioners regarding the survival of business in the present days of
uncertain manufacturing world. This paper assists the industrial
managers to consider all the important criteria for success AMT
implementation, when purchasing new technology. Concurrently,
this paper classifies the tangible benefits of a technology that are
evaluated by addressing both cost and time dimensions, and the
intangible benefits are evaluated by addressing technological,
strategic, social and human issues to identify and create awareness of
the essential elements in the AMT implementation process and
identify the necessary actions before implementing AMT.
Abstract: The interactions between input/output variables are a very common phenomenon encountered in the design of multi-loop controllers for interacting multivariable processes, which can be a serious obstacle for achieving a good overall performance of multiloop control system. To overcome this impediment, the decomposed dynamic interaction analysis is proposed by decomposing the multiloop control system into a set of n independent SISO systems with the corresponding effective open-loop transfer function (EOTF) within the dynamic interactions embedded explicitly. For each EOTF, the reduced model is independently formulated by using the proposed reduction design strategy, and then the paired multi-loop proportional-integral-derivative (PID) controller is derived quite simply and straightforwardly by using internal model control (IMC) theory. This design method can easily be implemented for various industrial processes because of its effectiveness. Several case studies are considered to demonstrate the superior of the proposed method.
Abstract: Large metal and concrete structures suffer by various kinds of deterioration, and accurate prediction of the remaining life is important. This paper informs about two methods for its assessment. One method, suitable for steel bridges and other constructions exposed to fatigue, monitors the loads and damage accumulation using information systems for the operation and the finite element model of the construction. In addition to the operation load, the dead weight of the construction and thermal stresses can be included into the model. The second method is suitable for concrete bridges and other structures, which suffer by carbonatation and other degradation processes, driven by diffusion. The diffusion constant, important for the prediction of future development, can be determined from the depth-profile of pH, obtained by pH measurement at various depths. Comparison with measurements on real objects illustrates the suitability of both methods.
Abstract: Air conditioning systems of houses consume large
quantity of electricity. To reducing energy consumption for air
conditioning purposes it is becoming attractive the use of evaporative
cooling air conditioning which is less energy consuming compared to
air chillers. But, it is obvious that higher energy efficiency of
evaporative cooling is not enough to judge whether evaporative
cooling economically is competitive with other types of cooling
systems. To proving the higher energy efficiency and cost
effectiveness of the evaporative cooling competitive analysis of
various types of cooling system should be accomplished. For noted
purpose optimization mathematical model for each system should be
composed based on system approach analysis. In this paper different
types of evaporative cooling-heating systems are discussed and
methods for increasing their energy efficiency and as well as
determining of their design parameters are developed. The
optimization mathematical models for each of them are composed
with help of which least specific costs for each of them are reviled.
The comparison of specific costs proved that the most efficient and
cost effective is considered the “direct evaporating" system if it is
applicable for given climatic conditions. Next more universal and
applicable for many climatic conditions system providing least cost
of heating and cooling is considered the “direct evaporating" system.
Abstract: Data mining can be called as a technique to extract
information from data. It is the process of obtaining hidden
information and then turning it into qualified knowledge by statistical
and artificial intelligence technique. One of its application areas is
medical area to form decision support systems for diagnosis just by
inventing meaningful information from given medical data. In this
study a decision support system for diagnosis of illness that make use
of data mining and three different artificial intelligence classifier
algorithms namely Multilayer Perceptron, Naive Bayes Classifier and
J.48. Pima Indian dataset of UCI Machine Learning Repository was
used. This dataset includes urinary and blood test results of 768
patients. These test results consist of 8 different feature vectors.
Obtained classifying results were compared with the previous studies.
The suggestions for future studies were presented.
Abstract: Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.
Abstract: In this research a mathematical model for direct
oxidization of hydrogen sulfide into elemental sulfur in a fluidized
bed reactor with external circulation was developed. As the catalyst
is deactivated in the fluidized bed, it might be placed in a reduction
tank in order to remove sulfur through heating above its dew point.
The reactor model demonstrated via MATLAB software. It was
shown that variations of H2S conversion as well as; products formed
were reasonable in comparison with corresponding results of a fixed
bed reactor. Through analyzing results of this model, it became
possible to propose the main optimized operating conditions for the
process considered. These conditions included; the temperature range
of 100-130ºC and utilizing the catalyst as much as possible providing
the highest bed density respect to dimensions of bed, economical
aspects that the bed ever remained in fluidized mode. A high active
and stable catalyst under the optimum conditions exhibited 100%
conversion in a fluidized bed reactor.
Abstract: The success of IT-projects concerning the
implementation of business application Software is strongly
depending upon the application of an efficient requirements
management, to understand the business requirements and to realize
them in the IT. But in fact, the Potentials of the requirements
management are not fully exhausted by small and medium sized
enterprises (SME) of the IT sector. To work out recommendations for
action and furthermore a possible solution, allowing a better exhaust
of potentials, it shall be examined in a scientific research project,
which problems occur out of which causes. In the same place, the
storage of knowledge from the requirements management, and its
later reuse are important, to achieve sustainable improvements of the
competitive of the IT-SMEs. Requirements Engineering is one of the
most important topics in Product Management for Software to
achieve the goal of optimizing the success of the software product.
Abstract: Macrophomina phaseolina is a devastating soil-borne
fungal plant pathogen that causes charcoal rot disease in many
economically important crops worldwide. So far, no registered
fungicide is available against this plant pathogen. This study was
planned to examine the antifungal activity of an allelopathic grass
Cenchrus pennisetiformis (Hochst. & Steud.) Wipff. for the
management of M. phaseolina isolated from cowpea [Vigna
unguiculata (L.) Walp.] plants suffering from charcoal rot disease.
Different parts of the plants viz. inflorescence, shoot and root were
extracted in methanol. Laboratory bioassays were carried out using
different concentrations (0, 0.5, 1.0, …, 3.0 g mL-1) of methanolic
extracts of the test allelopathic grass species to assess the antifungal
activity against the pathogen. In general, extracts of all parts of the
grass exhibited antifungal activity. All the concentrations of
methanolic extracts of shoot and root significantly reduced fungal
biomass by 20–73% and 40–80%, respectively. Methanolic shoot
extract was fractionated using n-hexane, chloroform, ethyl acetate
and n-butanol. Different concentrations of these fractions (3.125,
6.25, …, 200 mg mL-1) were analyzed for their antifungal activity.
All the concentrations of n-hexane fraction significantly reduced
fungal biomass by 15–96% over corresponding control treatments.
Higher concentrations (12.5–200 mg mL-1) of chloroform, ethyl
acetate and n-butanol also reduced the fungal biomass significantly
by 29–100%, 46–100% and 24–100%, respectively.
Abstract: management of medical devices in hospitals includes
the planning of medical equipment acquisition and maintenance. The
presence of critical and non-critical areas together with technological
proliferation render the management of medical devices very
complex. This study creates an easy and objective methodology for
the analysis of medical equipment maintenance, that makes the
management of medical devices more feasible. The study has been
carried out at Florence Hospital Careggi and it aims to help the
clinical engineering department to manage medical equipment by
clarifying the hospital situation through a characterization of the
different areas, technologies and fault typologies.
Abstract: Photo-crosslinked rice starch-based biodegradable
films were prepared by casting film-solution on leveled trays and
ultra violet (UV) irradiation was applied for 10 minute. The effect of
the content (3%, 6% and 9 wt. %)of photosensitiser (sodium
benzoate) on mechanical properties, water vapor permeability (WVP)
and structural properties of rice starch films were investigated. The
tensile strength increased while elongation at break and water
resistance properties of rice starch films decreased with addition and
increasing content of photosensitiser. The % crystallinity of rice
starch films were decreased when the content of photosensitiser
increased and UV were applied. The results showed that the
carboxylate group band of sodium benzoate was found in the FTIR
spectrum of rice starch films and found that incorporation of 6% of
photosensitiser into the films showed a higher absorption band of
resulted films. This result pointed out the highest interaction between
starch molecules was occurred.
Abstract: This paper is a review on the aspects and approaches of design an image cryptosystem. First a general introduction given for cryptography and images encryption and followed by different techniques in image encryption and related works for each technique surveyed. Finally, general security analysis methods for encrypted images are mentioned.
Abstract: The gases generated in oil filled transformers can be
used for qualitative determination of incipient faults. The Dissolved
Gas Analysis has been widely used by utilities throughout the world
as the primarily diagnostic tool for transformer maintenance. In this
paper, various Artificial Intelligence Techniques that have been used
by the researchers in the past have been reviewed, some conclusions
have been drawn and a sequential hybrid system has been proposed.
The synergy of ANN and FIS can be a good solution for reliable
results for predicting faults because one should not rely on a single
technology when dealing with real–life applications.
Abstract: This paper deals with condition monitoring of electric switch machine for railway points. Point machine, as a complex electro-mechanical device, switch the track between two alternative routes. There has been an increasing interest in railway safety and the optimal management of railway equipments maintenance, e.g. point machine, in order to enhance railway service quality and reduce system failure. This paper explores the development of Kolmogorov- Smirnov (K-S) test to detect some point failures (external to the machine, slide chairs, fixing, stretchers, etc), while the point machine (inside the machine) is in its proper condition. Time-domain stator Current signatures of normal (healthy) and faulty points are taken by 3 Hall Effect sensors and are analyzed by K-S test. The test is simulated by creating three types of such failures, namely putting a hard stone and a soft stone between stock rail and switch blades as obstacles and also slide chairs- friction. The test has been applied for those three faults which the results show that K-S test can effectively be developed for the aim of other point failures detection, which their current signatures deviate parametrically from the healthy current signature. K-S test as an analysis technique, assuming that any defect has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. This test works based on the null hypothesis that ECDF of target distribution is statistically similar to ECDF of reference distribution. Therefore by comparing a given current signature (as target signal) from unknown switch state to a number of template signatures (as reference signal) from known switch states, it is possible to identify which is the most likely state of the point machine under analysis.