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: Compression algorithms reduce the redundancy in
data representation to decrease the storage required for that data.
Lossless compression researchers have developed highly
sophisticated approaches, such as Huffman encoding, arithmetic
encoding, the Lempel-Ziv (LZ) family, Dynamic Markov
Compression (DMC), Prediction by Partial Matching (PPM), and
Burrows-Wheeler Transform (BWT) based algorithms.
Decompression is also required to retrieve the original data by
lossless means. A compression scheme for text files coupled with
the principle of dynamic decompression, which decompresses only
the section of the compressed text file required by the user instead of
decompressing the entire text file. Dynamic decompressed files offer
better disk space utilization due to higher compression ratios
compared to most of the currently available text file formats.
Abstract: In H.264/AVC video encoding, rate-distortion
optimization for mode selection plays a significant role to achieve
outstanding performance in compression efficiency and video quality.
However, this mode selection process also makes the encoding
process extremely complex, especially in the computation of the ratedistortion
cost function, which includes the computations of the sum
of squared difference (SSD) between the original and reconstructed
image blocks and context-based entropy coding of the block. In this
paper, a transform-domain rate-distortion optimization accelerator
based on fast SSD (FSSD) and VLC-based rate estimation algorithm
is proposed. This algorithm could significantly simplify the hardware
architecture for the rate-distortion cost computation with only
ignorable performance degradation. An efficient hardware structure
for implementing the proposed transform-domain rate-distortion
optimization accelerator is also proposed. Simulation results
demonstrated that the proposed algorithm reduces about 47% of total
encoding time with negligible degradation of coding performance.
The proposed method can be easily applied to many mobile video
application areas such as a digital camera and a DMB (Digital
Multimedia Broadcasting) phone.
Abstract: This article presents a computationally tractable probabilistic model for the relation between the complex wavelet coefficients of two images of the same scene. The two images are acquisitioned at distinct moments of times, or from distinct viewpoints, or by distinct sensors. By means of the introduced probabilistic model, we argue that the similarity between the two images is controlled not by the values of the wavelet coefficients, which can be altered by many factors, but by the nature of the wavelet coefficients, that we model with the help of hidden state variables. We integrate this probabilistic framework in the construction of a new image registration algorithm. This algorithm has sub-pixel accuracy and is robust to noise and to other variations like local illumination changes. We present the performance of our algorithm on various image types.
Abstract: Water 2H NMR signal on the surface of nano-silica material, MCM-41, consists of two overlapping resonances. The 2H water spectrum shows a superposition of a Lorentzian line shape and the familiar NMR powder pattern line shape, indicating the existence of two spin components. Chemical exchange occurs between these two groups. Decomposition of the two signals is a crucial starting point for study the exchange process. In this article we have determined these spin component populations along with other important parameters for the 2H water NMR signal over a temperature range between 223 K and 343 K.
Abstract: This paper describes an efficient and practical method
for economic dispatch problem in one and two area electrical power
systems with considering the constraint of the tie transmission line
capacity constraint. Direct search method (DSM) is used with some
equality and inequality constraints of the production units with any
kind of fuel cost function. By this method, it is possible to use several
inequality constraints without having difficulty for complex cost
functions or in the case of unavailability of the cost function
derivative. To minimize the number of total iterations in searching,
process multi-level convergence is incorporated in the DSM.
Enhanced direct search method (EDSM) for two area power system
will be investigated. The initial calculation step size that causes less
iterations and then less calculation time is presented. Effect of the
transmission tie line capacity, between areas, on economic dispatch
problem and on total generation cost will be studied; line
compensation and active power with reactive power dispatch are
proposed to overcome the high generation costs for this multi-area
system.
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: This paper suggests a new Affine Projection (AP) algorithm with variable data-reuse factor using the condition number as a decision factor. To reduce computational burden, we adopt a recently reported technique which estimates the condition number of an input data matrix. Several simulations show that the new algorithm has better performance than that of the conventional AP algorithm.
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: Metal matrix composites (MMC) are generating
extensive interest in diverse fields like defense, aerospace, electronics
and automotive industries. In this present investigation, material
removal rate (MRR) modeling has been carried out using an
axisymmetric model of Al-SiC composite during electrical discharge
machining (EDM). A FEA model of single spark EDM was
developed to calculate the temperature distribution.Further, single
spark model was extended to simulate the second discharge. For
multi-discharge machining material removal was calculated by
calculating the number of pulses. Validation of model has been done
by comparing the experimental results obtained under the same
process parameters with the analytical results. A good agreement was
found between the experimental results and the theoretical value.
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: In this paper, a method for matching image segments
using triangle-based (geometrical) regions is proposed. Triangular
regions are formed from triples of vertex points obtained from a
keypoint detector (SIFT). However, triangle regions are subject to
noise and distortion around the edges and vertices (especially acute
angles). Therefore, these triangles are expanded into parallelogramshaped
regions. The extracted image segments inherit an important
triangle property; the invariance to affine distortion. Given two
images, matching corresponding regions is conducted by computing
the relative affine matrix, rectifying one of the regions w.r.t. the other
one, then calculating the similarity between the reference and
rectified region. The experimental tests show the efficiency and
robustness of the proposed algorithm against geometrical distortion.
Abstract: Aluminum/Copper clad sheet has been fabricated using
asymmetric extrusion method, which caused severe shear deformation
between Al and Cu plate to easily bond to each other. Interfacial
microstructure and mechanical properties of Al/Cu clad were studied
by scanning electron microscope equipped with energy dispersive
X-ray detector, micro-hardness, and tension tests. The asymmetric
extrusion bonding was very effective to provide a good interface for
atoms diffusion during subsequent annealing. The strength of bonding
was higher with the increasing extrusion ratio.
Abstract: In the study the influence of the physical-chemical properties of a liquid, the width of a channel gap and the superficial liquid and gas velocities on the patterns formed during two phase flows in vertical, narrow mini-channels was investigated. The research was performed in the channels of rectangular cross-section and of dimensions: 15 x 0.65 mm and 7.5 x 0.73 mm. The experimental data were compared with the published criteria of the transitions between the patterns of two-phase flows.
Abstract: Packet switched data network like Internet, which has
traditionally supported throughput sensitive applications such as email
and file transfer, is increasingly supporting delay-sensitive
multimedia applications such as interactive video. These delaysensitive
applications would often rather sacrifice some throughput
for better delay. Unfortunately, the current packet switched network
does not offer choices, but instead provides monolithic best-effort
service to all applications. This paper evaluates Class Based Queuing
(CBQ), Coordinated Earliest Deadline First (CEDF), Weighted
Switch Deficit Round Robin (WSDRR) and RED-Boston scheduling
schemes that is sensitive to delay bound expectations for variety of
real time applications and an enhancement of WSDRR is proposed.
Abstract: The study is aimed to test causal relationship between
growth and unemployment, using time series data for Pakistan from
1972 to 2006. Growth is considered to be a pathway to decrease the
level of unemployment. Unemployment is a social and political
issue. It is a phenomenon where human resources are wasted leading
to deacceleration in growth. Johanson Cointegration shows that there
is long run relationship between growth and unemployment. For
short run dynamics and causality, the study utilizes Vector Error
Correction Model (VECM). The results of VECM indicate that there
is short and long run causal relation between growth and
unemployment including capital, labor and human capital as
explanatory variables.
Abstract: In this paper, we analyze the rotor eddy currents losses provoqued by the stator slot harmonics developed in the permanent magnets or pole pieces of synchronous machines. An analytical approach is presented to evaluate the effect of slot ripples on rotor field and losses calculation. This analysis is then tested on a model by 2D/3D finite element (FE) calculation. The results show a good agreement on loss calculations when skin effect is negligible and the magnet is considered.
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: A new approach to promote the generalization ability
of neural networks is presented. It is based on the point of view of
fuzzy theory. This approach is implemented through shrinking or
magnifying the input vector, thereby reducing the difference between
training set and testing set. It is called “shrinking-magnifying
approach" (SMA). At the same time, a new algorithm; α-algorithm is
presented to find out the appropriate shrinking-magnifying-factor
(SMF) α and obtain better generalization ability of neural networks.
Quite a few simulation experiments serve to study the effect of SMA
and α-algorithm. The experiment results are discussed in detail, and
the function principle of SMA is analyzed in theory. The results of
experiments and analyses show that the new approach is not only
simpler and easier, but also is very effective to many neural networks
and many classification problems. In our experiments, the proportions
promoting the generalization ability of neural networks have even
reached 90%.
Abstract: The frontal area in the brain is known to be involved in
behavioral judgement. Because a Kanji character can be discriminated
visually and linguistically from other characters, in Kanji character
discrimination, we hypothesized that frontal event-related potential
(ERP) waveforms reflect two discrimination processes in separate
time periods: one based on visual analysis and the other based
on lexcical access. To examine this hypothesis, we recorded ERPs
while performing a Kanji lexical decision task. In this task, either a
known Kanji character, an unknown Kanji character or a symbol was
presented and the subject had to report if the presented character was
a known Kanji character for the subject or not. The same response
was required for unknown Kanji trials and symbol trials. As a preprocessing
of signals, we examined the performance of a method
using independent component analysis for artifact rejection and found
it was effective. Therefore we used it. In the ERP results, there
were two time periods in which the frontal ERP wavefoms were
significantly different betweeen the unknown Kanji trials and the
symbol trials: around 170ms and around 300ms after stimulus onset.
This result supported our hypothesis. In addition, the result suggests
that Kanji character lexical access may be fully completed by around
260ms after stimulus onset.