Abstract: The genus Fumaria L. (Papaveraceae) in Iran
comprises 8 species with a vast medicinal use in Asian folk
medicine. These herbs are considered to be useful in the
treatment of gastrointestinal disease and skin disorders.
Antioxidant activities of alkaloids and phenolic extracts of
these species had been studied previously. These species are:
F. officinalis, F. parviflora, F. asepala, F. densiflora, F.
schleicheri, F. vaillantii and F. indica. More than 50
populations of Fumaria species were sampled from nature. In
this study different fatty acids are extracted. Their picks were
recorded by GC technique. This species contain some kind of
fatty acids with antioxidant effects. A part of these lipids are
phospholipids. As these are unsaturated fatty acids they may
have industrial use as natural additive to cosmetics, dermal
and oral medicines. The presences of different materials are
discussed. Our studies for antioxidant effects of these
substances are continued.
Abstract: The paper presents a space-vector pulse width modulation (SVPWM) inverter feeding a permanent-magnet synchronous motor (PMSM). The SVPWM inverter enables to feed the motor with a higher voltage with low harmonic distortions than the conventional sinusoidal PWM inverter. The control strategy of the inverter is the voltage / frequency control method, which is based on the space-vector modulation technique. The proposed PMSM drive system involving the field-oriented control scheme not only decouples the torque and flux which provides faster response but also makes the control task easy. The performance of the proposed drive is simulated. The advantages of the proposed drive are confirmed by the simulation results.
Abstract: The method of gait identification based on the nearest neighbor classification technique with motion similarity assessment by the dynamic time warping is proposed. The model based kinematic motion data, represented by the joints rotations coded by Euler angles and unit quaternions is used. The different pose distance functions in Euler angles and quaternion spaces are considered. To evaluate individual features of the subsequent joints movements during gait cycle, joint selection is carried out. To examine proposed approach database containing 353 gaits of 25 humans collected in motion capture laboratory is used. The obtained results are promising. The classifications, which takes into consideration all joints has accuracy over 91%. Only analysis of movements of hip joints allows to correctly identify gaits with almost 80% precision.
Abstract: In high bitrate information hiding techniques, 1 bit is
embedded within each 4 x 4 Discrete Cosine Transform (DCT)
coefficient block by means of vector quantization, then the hidden bit
can be effectively extracted in terminal end. In this paper high bitrate
information hiding algorithms are summarized, and the scheme of
video in video is implemented. Experimental result shows that the host
video which is embedded numerous auxiliary information have little
visually quality decline. Peak Signal to Noise Ratio (PSNR)Y of host
video only degrades 0.22dB in average, while the hidden information
has a high percentage of survives and keeps a high robustness in
H.264/AVC compression, the average Bit Error Rate(BER) of hiding
information is 0.015%.
Abstract: Pattern matching is one of the fundamental applications in molecular biology. Searching DNA related data is a common activity for molecular biologists. In this paper we explore the applicability of a new pattern matching technique called Index based Forward Backward Multiple Pattern Matching algorithm(IFBMPM), for DNA Sequences. Our approach avoids unnecessary comparisons in the DNA Sequence due to this; the number of comparisons of the proposed algorithm is very less compared to other existing popular methods. The number of comparisons rapidly decreases and execution time decreases accordingly and shows better performance.
Abstract: Bloom filter is a probabilistic and memory efficient
data structure designed to answer rapidly whether an element is
present in a set. It tells that the element is definitely not in the set but
its presence is with certain probability. The trade-off to use Bloom
filter is a certain configurable risk of false positives. The odds of a
false positive can be made very low if the number of hash function is
sufficiently large. For spam detection, weight is attached to each set
of elements. The spam weight for a word is a measure used to rate the
e-mail. Each word is assigned to a Bloom filter based on its weight.
The proposed work introduces an enhanced concept in Bloom filter
called Bin Bloom Filter (BBF). The performance of BBF over
conventional Bloom filter is evaluated under various optimization
techniques. Real time data set and synthetic data sets are used for
experimental analysis and the results are demonstrated for bin sizes 4,
5, 6 and 7. Finally analyzing the results, it is found that the BBF
which uses heuristic techniques performs better than the traditional
Bloom filter in spam detection.
Abstract: It is well known that the channel capacity of Multiple-
Input-Multiple-Output (MIMO) system increases as the number of
antenna pairs between transmitter and receiver increases but it suffers
from multiple expensive RF chains. To reduce the cost of RF chains,
Antenna Selection (AS) method can offer a good tradeoff between
expense and performance. In a transmitting AS system, Channel
State Information (CSI) feedback is necessarily required to choose
the best subset of antennas in which the effects of delays and errors
occurred in feedback channels are the most dominant factors
degrading the performance of the AS method. This paper presents the
concept of AS method using CSI from channel reciprocity instead of
feedback method. Reciprocity technique can easily archive CSI by
utilizing a reverse channel where the forward and reverse channels
are symmetrically considered in time, frequency and location. In this
work, the capacity performance of MIMO system when using AS
method at transmitter with reciprocity channels is investigated by
own developing Testbed. The obtained results show that reciprocity
technique offers capacity close to a system with a perfect CSI and
gains a higher capacity than a system without AS method from 0.9 to
2.2 bps/Hz at SNR 10 dB.
Abstract: The purpose of this paper is to assess the value of neural networks for classification of cancer and noncancer prostate cells. Gauss Markov Random Fields, Fourier entropy and wavelet average deviation features are calculated from 80 noncancer and 80 cancer prostate cell nuclei. For classification, artificial neural network techniques which are multilayer perceptron, radial basis function and learning vector quantization are used. Two methods are utilized for multilayer perceptron. First method has single hidden layer and between 3-15 nodes, second method has two hidden layer and each layer has between 3-15 nodes. Overall classification rate of 86.88% is achieved.
Abstract: Preparation of size controlled nano-particles of silver catalyst on carbon substrate from e-waste has been investigated. Chemical route was developed by extraction of the metals available in nitric acid followed by treatment with hydrofluoric acid. Silver metal particles deposited with an average size 4-10 nm. A stabilizer concentration of 10- 40 g/l was used. The average size of the prepared silver decreased with increase of the anode current density. Size uniformity of the silver nano-particles was improved distinctly at higher current density no more than 20mA... Grain size increased with EK time whereby aggregation of particles was observed after 6 h of reaction.. The chemical method involves adsorption of silver nitrate on the carbon substrate. Adsorbed silver ions were directly reduced to metal particles using hydrazine hydrate. Another alternative method is by treatment with ammonia followed by heating the carbon loaded-silver hydroxide at 980°C. The product was characterized with the help of XRD, XRF, ICP, SEM and TEM techniques.
Abstract: The current work focuses on rephrasing the harmful
effects of mercury that is being released from a number of sources.
Most of the sources are from the industrial waste water. Different
techniques of mercury removal have been discussed and a brief
comparison among these has been made. The experimental work has
been conducted for two most widely used methods of mercury
removal and comparison in terms of their efficiency has been made.
Abstract: Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows drawing conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stageby- stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.
Abstract: With a surge of stream processing applications novel
techniques are required for generation and analysis of association
rules in streams. The traditional rule mining solutions cannot handle
streams because they generally require multiple passes over the data
and do not guarantee the results in a predictable, small time. Though
researchers have been proposing algorithms for generation of rules
from streams, there has not been much focus on their analysis.
We propose Association rule profiling, a user centric process for
analyzing association rules and attaching suitable profiles to them
depending on their changing frequency behavior over a previous
snapshot of time in a data stream.
Association rule profiles provide insights into the changing nature
of associations and can be used to characterize the associations. We
discuss importance of characteristics such as predictability of
linkages present in the data and propose metric to quantify it. We
also show how association rule profiles can aid in generation of user
specific, more understandable and actionable rules.
The framework is implemented as SUPAR: System for Usercentric
Profiling of Association Rules in streaming data. The
proposed system offers following capabilities:
i) Continuous monitoring of frequency of streaming item-sets
and detection of significant changes therein for association rule
profiling.
ii) Computation of metrics for quantifying predictability of
associations present in the data.
iii) User-centric control of the characterization process: user
can control the framework through a) constraint specification and b)
non-interesting rule elimination.
Abstract: An attempt has been made to investigate the
machinability of zirconia toughened alumina (ZTA) inserts while
turning AISI 4340 steel. The insert was prepared by powder
metallurgy process route and the machining experiments were
performed based on Response Surface Methodology (RSM) design
called Central Composite Design (CCD). The mathematical model of
flank wear, cutting force and surface roughness have been developed
using second order regression analysis. The adequacy of model has
been carried out based on Analysis of variance (ANOVA) techniques.
It can be concluded that cutting speed and feed rate are the two most
influential factor for flank wear and cutting force prediction. For
surface roughness determination, the cutting speed & depth of cut
both have significant contribution. Key parameters effect on each
response has also been presented in graphical contours for choosing
the operating parameter preciously. 83% desirability level has been
achieved using this optimized condition.
Abstract: Design and implementation of a novel B-ACOSD CFAR algorithm is presented in this paper. It is proposed for detecting radar target in log-normal distribution environment. The BACOSD detector is capable to detect automatically the number interference target in the reference cells and detect the real target by an adaptive threshold. The detector is implemented as a System on Chip on FPGA Altera Stratix II using parallelism and pipelining technique. For a reference window of length 16 cells, the experimental results showed that the processor works properly with a processing speed up to 115.13MHz and processing time0.29 ┬Ás, thus meets real-time requirement for a typical radar system.
Abstract: This paper presents the effectiveness of artificial
intelligent technique to apply for pattern recognition and
classification of Partial Discharge (PD). Characteristics of PD signal
for pattern recognition and classification are computed from the
relation of the voltage phase angle, the discharge magnitude and the
repeated existing of partial discharges by using statistical and fractal
methods. The simplified fuzzy ARTMAP (SFAM) is used for pattern
recognition and classification as artificial intelligent technique. PDs
quantities, 13 parameters from statistical method and fractal method
results, are inputted to Simplified Fuzzy ARTMAP to train system
for pattern recognition and classification. The results confirm the
effectiveness of purpose technique.
Abstract: This paper presents three-phase evolution search methodology to automatically design fuzzy logic controllers (FLCs) that can work in a wide range of operating conditions. These include varying load, parameter variations, and unknown external disturbances. The three-phase scheme consists of an exploration phase, an exploitation phase and a robustness phase. The first two phases search for FLC with high accuracy performances while the last phase aims at obtaining FLC providing the best compromise between the accuracy and robustness performances. Simulations were performed for direct-drive two-axis robot arm. The evolved FLC with the proposed design technique found to provide a very satisfactory performance under the wide range of operation conditions and to overcome problem associated with coupling and nonlinearities characteristics inherent to robot arms.
Abstract: Feature selection plays an important role in applications with high dimensional data. The assessment of the stability of feature selection/ranking algorithms becomes an important issue when the dataset is small and the aim is to gain insight into the underlying process by analyzing the most relevant features. In this work, we propose a graphical approach that enables to analyze the similarity between feature ranking techniques as well as their individual stability. Moreover, it works with whatever stability metric (Canberra distance, Spearman's rank correlation coefficient, Kuncheva's stability index,...). We illustrate this visualization technique evaluating the stability of several feature selection techniques on a spectral binary dataset. Experimental results with a neural-based classifier show that stability and ranking quality may not be linked together and both issues have to be studied jointly in order to offer answers to the domain experts.
Abstract: In this paper we propose a novel method for human
face segmentation using the elliptical structure of the human head. It
makes use of the information present in the edge map of the image.
In this approach we use the fact that the eigenvalues of covariance
matrix represent the elliptical structure. The large and small
eigenvalues of covariance matrix are associated with major and
minor axial lengths of an ellipse. The other elliptical parameters are
used to identify the centre and orientation of the face. Since an
Elliptical Hough Transform requires 5D Hough Space, the Circular
Hough Transform (CHT) is used to evaluate the elliptical parameters.
Sparse matrix technique is used to perform CHT, as it squeeze zero
elements, and have only a small number of non-zero elements,
thereby having an advantage of less storage space and computational
time. Neighborhood suppression scheme is used to identify the valid
Hough peaks. The accurate position of the circumference pixels for
occluded and distorted ellipses is identified using Bresenham-s
Raster Scan Algorithm which uses the geometrical symmetry
properties. This method does not require the evaluation of tangents
for curvature contours, which are very sensitive to noise. The method
has been evaluated on several images with different face orientations.
Abstract: In the course of the present work, plain (nonencapsulated)
and microencapsulated polyphenols were produced
using olive mill wastewater (OMW) as raw material, in order to be
used for enrichment of yogurt and dairy products. The OMW was
first clarified by using membrane technology and subsequently the
contained poly-phenols were isolated by adsorption-desorption
technique using selective macro-porous resins and finally recovered
in dry form after been processed by RO membrane technique
followed by freeze drying. Moreover, the polyphenols were
encapsulated in modified starch by freeze drying in order to mask the
color and bitterness effect and improve their functionality. The two
products were used successfully as additives in yogurt preparations
and the produced products were acceptable by the consumers and
presented with certain advantage to the plain yogurt. For the herein
proposed production scheme a patent application was already
submitted.
Abstract: Prior research evidenced that unimodal biometric
systems have several tradeoffs like noisy data, intra-class variations,
restricted degrees of freedom, non-universality, spoof attacks, and
unacceptable error rates. In order for the biometric system to be more
secure and to provide high performance accuracy, more than one
form of biometrics are required. Hence, the need arise for multimodal
biometrics using combinations of different biometric modalities. This
paper introduces a multimodal biometric system (MMBS) based on
fusion of whole dorsal hand geometry and fingerprints that acquires
right and left (Rt/Lt) near-infra-red (NIR) dorsal hand geometry (HG)
shape and (Rt/Lt) index and ring fingerprints (FP). Database of 100
volunteers were acquired using the designed prototype. The acquired
images were found to have good quality for all features and patterns
extraction to all modalities. HG features based on the hand shape
anatomical landmarks were extracted. Robust and fast algorithms for
FP minutia points feature extraction and matching were used. Feature
vectors that belong to similar biometric traits were fused using
feature fusion methodologies. Scores obtained from different
biometric trait matchers were fused using the Min-Max
transformation-based score fusion technique. Final normalized scores
were merged using the sum of scores method to obtain a single
decision about the personal identity based on multiple independent
sources. High individuality of the fused traits and user acceptability
of the designed system along with its experimental high performance
biometric measures showed that this MMBS can be considered for
med-high security levels biometric identification purposes.