Abstract: In order to accommodate various multimedia
services, next generation wireless networks are characterized
by very high transmission bit rates. Thus, in such systems and
networks, the received signal is not only limited by noise but -
especially with increasing symbols rate often more
significantly by the intersymbol interference (ISI) caused by
the time dispersive radio channels such as those are used in
this work. This paper deals with the study of the performance
of detector for high bit rate transmission on some worst case
models of frequency selective fading channels for outdoor
mobile radio environments. This paper deals with a number of
different wireless channels with different power profiles and
different number of resolvable paths. All the radio channels
generated in this paper are for outdoor vehicular environments
with Doppler spread of 100 Hz. A carrier frequency of 1800
MHz is used and all the channels used in this work are such
that they are useful for next generation wireless systems.
Schemes for mitigation of ISI with adaptive equalizers of
different types have been investigated and their performances
have been investigated in terms of BER measured as a function
of SNR.
Abstract: In this paper, we propose a selective mutation method
for improving the performances of genetic algorithms. In selective
mutation, individuals are first ranked and then additionally mutated
one bit in a part of their strings which is selected corresponding to
their ranks. This selective mutation helps genetic algorithms to fast
approach the global optimum and to quickly escape local optima.
This results in increasing the performances of genetic algorithms.
We measured the effects of selective mutation with four function
optimization problems. It was found from extensive experiments that
the selective mutation can significantly enhance the performances of
genetic algorithms.
Abstract: In the field of concepts, the measure of Wu and Palmer [1] has the advantage of being simple to implement and have good performances compared to the other similarity measures [2]. Nevertheless, the Wu and Palmer measure present the following disadvantage: in some situations, the similarity of two elements of an IS-A ontology contained in the neighborhood exceeds the similarity value of two elements contained in the same hierarchy. This situation is inadequate within the information retrieval framework. To overcome this problem, we propose a new similarity measure based on the Wu and Palmer measure. Our objective is to obtain realistic results for concepts not located in the same way. The obtained results show that compared to the Wu and Palmer approach, our measure presents a profit in terms of relevance and execution time.
Abstract: This study reports the preparation of soft magnetic
ribbons of Fe-based amorphous alloys using the single-roller melt-spinning technique. Ribbon width varied from 142 mm to 213
mm and, with a thickness of approximately 22 μm ± 2 μm. The microstructure and magnetic properties of the ribbons were
characterized by differential scanning calorimeter (DSC), X-ray diffraction (XRD), vibrating sample magnetometer (VSM), and electrical resistivity measurements (ERM). The amorphous material
properties dependence of the cooling rate and nozzle pressure have uneven surface in ribbon thicknesses are investigated. Magnetic
measurement results indicate that some region of the ribbon exhibits good magnetic properties, higher saturation induction and lower coercivity. However, due to the uneven surface of 213 mm wide
ribbon, the magnetic responses are not uniformly distributed. To
understand the transformer magnetic performances, this study analyzes the measurements of a three-phase 2 MVA amorphous-cored transformer. Experimental results confirm that the transformer with a
ribbon width of 142 mm has better magnetic properties in terms of lower core loss, exciting power, and audible noise.
Abstract: This paper presents and evaluates a new classification
method that aims to improve classifiers performances and speed up
their training process. The proposed approach, called labeled
classification, seeks to improve convergence of the BP (Back
propagation) algorithm through the addition of an extra feature
(labels) to all training examples. To classify every new example, tests
will be carried out each label. The simplicity of implementation is the
main advantage of this approach because no modifications are
required in the training algorithms. Therefore, it can be used with
others techniques of acceleration and stabilization. In this work, two
models of the labeled classification are proposed: the LMLP
(Labeled Multi Layered Perceptron) and the LNFC (Labeled Neuro
Fuzzy Classifier). These models are tested using Iris, wine, texture
and human thigh databases to evaluate their performances.
Abstract: This paper proposes an effective adaptation learning
algorithm based on artificial neural networks for speed control of an
induction motor assumed to operate in a high-performance drives
environment. The structure scheme consists of a neural network
controller and an algorithm for changing the NN weights in order that
the motor speed can accurately track of the reference command. This
paper also makes uses a very realistic and practical scheme to
estimate and adaptively learn the noise content in the speed load
torque characteristic of the motor. The availability of the proposed
controller is verified by through a laboratory implementation and
under computation simulations with Matlab-software. The process is
also tested for the tracking property using different types of reference
signals. The performance and robustness of the proposed control
scheme have evaluated under a variety of operating conditions of the
induction motor drives. The obtained results demonstrate the
effectiveness of the proposed control scheme system performances,
both in steady state error in speed and dynamic conditions, was found
to be excellent and those is not overshoot.
Abstract: Traffic management in an urban area is highly facilitated by the knowledge of the traffic conditions in every street or highway involved in the vehicular mobility system. Aim of the paper is to propose a neuro-fuzzy approach able to compute the main parameters of a traffic system, i.e., car density, velocity and flow, by using the images collected by the web-cams located at the crossroads of the traffic network. The performances of this approach encourage its application when the traffic system is far from the saturation. A fuzzy model is also outlined to evaluate when it is suitable to use more accurate, even if more time consuming, algorithms for measuring traffic conditions near to saturation.
Abstract: Multiphasing of dc-dc converters has been known to give technical and economical benefits to low voltage high power buck regulator modules. A major advantage of multiphasing dc-dc converters is the improvement of input and output performances in the buck converter. From this aspect, a potential use would be in renewable energy where power quality plays an important factor. This paper presents the design of a 2-phase 200W boost converter for battery charging application. Analysis of results from hardware measurement of the boost converter demonstrates the benefits of using multiphase. Results from the hardware prototype of the 2-phase boost converter further show the potential extension of multiphase beyond its commonly used low voltage high current domains.
Abstract: The Globally Asynchronous Locally Synchronous Network on Chip (GALS NoC) is the most efficient solution that provides low latency transfers and power efficient System on Chip (SoC) interconnect. This study presents a GALS and generic NoC architecture based on a configurable router. This router integrates a sophisticated dynamic arbiter, the wormhole routing technique and can be configured in a manner that allows it to be used in many possible NoC topologies such as Mesh 2-D, Tree and Polygon architectures. This makes it possible to improve the quality of service (QoS) required by the proposed NoC. A comparative performances study of the proposed NoC architecture, Tore architecture and of the most used Mesh 2D architecture is performed. This study shows that Spidergon architecture is characterised by the lower latency and the later saturation. It is also shown that no matter what the number of used links is raised; the Links×Diameter product permitted by the Spidergon architecture remains always the lower. The only limitation of this architecture comes from it-s over cost in term of silicon area.
Abstract: The performance of a type of fuzzy sliding mode control is researched by considering the nonlinear characteristic of a missile-target interception problem to obtain a robust interception process. The variable boundary layer by using fuzzy logic is proposed to reduce the chattering around the switching surface then is applied to the interception model which was derived. The performances of the sliding mode control with constant and fuzzy boundary layer are compared at the end of the study and the results are evaluated.
Abstract: A state of the art Speaker Identification (SI) system
requires a robust feature extraction unit followed by a speaker
modeling scheme for generalized representation of these features.
Over the years, Mel-Frequency Cepstral Coefficients (MFCC)
modeled on the human auditory system has been used as a standard
acoustic feature set for speech related applications. On a recent
contribution by authors, it has been shown that the Inverted Mel-
Frequency Cepstral Coefficients (IMFCC) is useful feature set for
SI, which contains complementary information present in high
frequency region. This paper introduces the Gaussian shaped filter
(GF) while calculating MFCC and IMFCC in place of typical
triangular shaped bins. The objective is to introduce a higher
amount of correlation between subband outputs. The performances
of both MFCC & IMFCC improve with GF over conventional
triangular filter (TF) based implementation, individually as well as
in combination. With GMM as speaker modeling paradigm, the
performances of proposed GF based MFCC and IMFCC in
individual and fused mode have been verified in two standard
databases YOHO, (Microphone Speech) and POLYCOST
(Telephone Speech) each of which has more than 130 speakers.
Abstract: This paper focuses on the Mega-Sub Controlled
Structure Systems (MSCSS) performances and characteristics
regarding the new control principle contained in MSCSS subjected to
strong earthquake excitations. The adopted control scheme consists of
modulated sub-structures where the control action is achieved by
viscous dampers and sub-structure own configuration. The
elastic-plastic time history analysis under severe earthquake excitation
is analyzed base on the Finite Element Analysis Method (FEAM), and
some comparison results are also given in this paper. The result shows
that the MSCSS systems can remarkably reduce vibrations effects
more than the mega-sub structure (MSS). The study illustrates that the
improved MSCSS presents good seismic resistance ability even at 1.2g
and can absorb seismic energy in the structure, thus imply that
structural members cross section can be reduce and achieve to good
economic characteristics. Furthermore, the elasto-plastic analysis
demonstrates that the MSCSS is accurate enough regarding
international building evaluation and design codes. This paper also
shows that the elasto-plastic dynamic analysis method is a reasonable
and reliable analysis method for structures subjected to strong
earthquake excitations and that the computed results are more precise.
Abstract: For Romania, the fulfilment of the obligations
undertaken as a member state of the European Union in accordance
with the Treaty of Accession requires the effective implementation of
sustainable development principles and practices, this being the only
reasonable development option, which adequately draws in on the
economic, social and environment resources. Achieving this
objective is based on a profound analysis of the realities in the
Romanian economy, which will reflect the existent situation and the
action directions for the future. The paper presents an analysis of the
Romanian economic performances compared to the EU economy,
based on the sustainable value (SV) model. The analysis highlighted
the considerable gap between Romania and the EU regarding the
sustainable capitalization of resources, the provided information
being useful to justify strategic development decisions at a micro and
macro levels.
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: For many chemical and biological processes, the understanding of the mixing phenomenon and flow behavior in a stirred tank is of major importance. A three-dimensional numerical study was performed using the software Fluent, to study the flow field in a stirred tank with a Rushton turbine. In this work, we first studied the flow generated in the tank with a Rushton turbine. Then, we studied the effect of the variation of turbine’s submergence on the thermodynamic quantities defining the flow field. For that, four submergences were considered, while maintaining the same rotational speed (N =250rpm). This work intends to optimize the aeration performances of a Rushton turbine in a stirred tank.
Abstract: Grobner basis calculation forms a key part of computational
commutative algebra and many other areas. One important
ramification of the theory of Grobner basis provides a means to solve
a system of non-linear equations. This is why it has become very
important in the areas where the solution of non-linear equations is
needed, for instance in algebraic cryptanalysis and coding theory. This
paper explores on a parallel-distributed implementation for Grobner
basis calculation over GF(2). For doing so Buchberger algorithm is
used. OpenMP and MPI-C language constructs have been used to
implement the scheme. Some relevant results have been furnished
to compare the performances between the standalone and hybrid
(parallel-distributed) implementation.
Abstract: This paper presents an new vision technique for
robotic manipulation of randomly oriented objects in industrial
applications. The proposed approach uses 2D and 3D vision for
efficiently extracting the 3D pose of an object in the presence of
multiple randomly positioned objects. 2D vision permits to quickly
select the objects of interest for 3D processing with a new modified
ICP algorithm (FaR-ICP), thus reducing significantly the processing
time. The extracted 3D pose is then sent to the robot manipulator for
picking. The tests show that the proposed system achieves high
performances
Abstract: In order to accelerate the similarity search in highdimensional database, we propose a new hierarchical indexing method. It is composed of offline and online phases. Our contribution concerns both phases. In the offline phase, after gathering the whole of the data in clusters and constructing a hierarchical index, the main originality of our contribution consists to develop a method to construct bounding forms of clusters to avoid overlapping. For the online phase, our idea improves considerably performances of similarity search. However, for this second phase, we have also developed an adapted search algorithm. Our method baptized NOHIS (Non-Overlapping Hierarchical Index Structure) use the Principal Direction Divisive Partitioning (PDDP) as algorithm of clustering. The principle of the PDDP is to divide data recursively into two sub-clusters; division is done by using the hyper-plane orthogonal to the principal direction derived from the covariance matrix and passing through the centroid of the cluster to divide. Data of each two sub-clusters obtained are including by a minimum bounding rectangle (MBR). The two MBRs are directed according to the principal direction. Consequently, the nonoverlapping between the two forms is assured. Experiments use databases containing image descriptors. Results show that the proposed method outperforms sequential scan and SRtree in processing k-nearest neighbors.
Abstract: In this paper a numerical technique is used to predict
the metal temperature of a gas turbine vane. The Rising combustor
exit temperatures in gas turbine engines necessitate active cooling for
the downstream turbine section to avoid thermal failure. This study is
performed the solution of external flow, internal convection, and
conduction within the metal vane. Also the trade-off between the
cooling performances in four different hole shapes and configurations
is performed. At first one of the commonly used cooling hole
geometry is investigated; cylindrical holes and then two other
configurations are simulated. The average temperature magnitude in
mid-plan section of each configuration is obtained and finally the
lower temperature value is selected such as best arrangement.
Abstract: This paper proposes new enhancement models to the
methods of nonlinear anisotropic diffusion to greatly reduce speckle
and preserve image features in medical ultrasound images. By
incorporating local physical characteristics of the image, in this case
scatterer density, in addition to the gradient, into existing tensorbased
image diffusion methods, we were able to greatly improve the
performance of the existing filtering methods, namely edge
enhancing (EE) and coherence enhancing (CE) diffusion. The new
enhancement methods were tested using various ultrasound images,
including phantom and some clinical images, to determine the
amount of speckle reduction, edge, and coherence enhancements.
Scatterer density weighted nonlinear anisotropic diffusion
(SDWNAD) for ultrasound images consistently outperformed its
traditional tensor-based counterparts that use gradient only to weight
the diffusivity function. SDWNAD is shown to greatly reduce
speckle noise while preserving image features as edges, orientation
coherence, and scatterer density. SDWNAD superior performances
over nonlinear coherent diffusion (NCD), speckle reducing
anisotropic diffusion (SRAD), adaptive weighted median filter
(AWMF), wavelet shrinkage (WS), and wavelet shrinkage with
contrast enhancement (WSCE), make these methods ideal
preprocessing steps for automatic segmentation in ultrasound
imaging.