Abstract: Recent developments in storage technology and
networking architectures have made it possible for broad areas of applications to rely on data streams for quick response and accurate
decision making. Data streams are generated from events of real world so existence of associations, which are among the occurrence of these events in real world, among concepts of data streams is
logical. Extraction of these hidden associations can be useful for prediction of subsequent concepts in concept shifting data streams. In this paper we present a new method for learning association among
concepts of data stream and prediction of what the next concept will be. Knowing the next concept, an informed update of data model will be possible. The results of conducted experiments show that the proposed method is proper for classification of concept shifting data
streams.
Abstract: The paper proposes a novel technique for iris
recognition using texture and phase features. Texture features are
extracted on the normalized iris strip using Haar Wavelet while phase
features are obtained using LOG Gabor Wavelet. The matching
scores generated from individual modules are combined using sum of
score technique. The system is tested on database obtained from Bath
University and Indian Institute of Technology Kanpur and is giving
an accuracy of 95.62% and 97.66% respectively. The FAR and FRR
of the combined system is also reduced comparatively.
Abstract: As emails communications have no consistent
authentication procedure to ensure the authenticity, we present an
investigation analysis approach for detecting forged emails based on
Random Forests and Naïve Bays classifiers. Instead of investigating
the email headers, we use the body content to extract a unique writing
style for all the possible suspects. Our approach consists of four main
steps: (1) The cybercrime investigator extract different effective
features including structural, lexical, linguistic, and syntactic
evidence from previous emails for all the possible suspects, (2) The
extracted features vectors are normalized to increase the accuracy
rate. (3) The normalized features are then used to train the learning
engine, (4) upon receiving the anonymous email (M); we apply the
feature extraction process to produce a feature vector. Finally, using
the machine learning classifiers the email is assigned to one of the
suspects- whose writing style closely matches M. Experimental
results on real data sets show the improved performance of the
proposed method and the ability of identifying the authors with a
very limited number of features.
Abstract: Two seperate experiments by barley and alfalfa were
conducted to a 2×8 factorial completely randomised design, with four
replicates. Factors were inoculation (M) with Gomus mosseae or uninoculation
(M0) and seven levels of contaminants (Co, Cd, Pb and
combinations) plus an uncontaminated control treatment (C). Heavy
metals in plant tissues and soil were quantified by Inductively
Coupled Plasma Optical Emission Spectrometer (ICP-OES) (Variant-
Liberty 150AX Turbo). Phytoextraction coefficient of contaminants
calculated by concentration of heavy metals in the shoot (mgkg-1) /
concentration of heavy metals in soil (mgkg-1). In the barley, the
highest rate of phytoextraction coefficient of Pb, Cd and Co was in
M0Pb, M0PbCoCd and MCo, respectively (P
Abstract: Face Recognition is a field of multidimensional
applications. A lot of work has been done, extensively on the most of
details related to face recognition. This idea of face recognition using
PCA is one of them. In this paper the PCA features for Feature
extraction are used and matching is done for the face under
consideration with the test image using Eigen face coefficients. The
crux of the work lies in optimizing Euclidean distance and paving the
way to test the same algorithm using Matlab which is an efficient tool
having powerful user interface along with simplicity in representing
complex images.
Abstract: The present work presents the extraction of copper(II)
from sulphuric acid solutions with Sodium diethyldithiocarbamate
(SDDT), and six different organic diluents: Dichloromethane,
Chloroform, Carbon tetrachloride, Toluene, xylene and Cyclohexane,
were tested. The pair SDDT/Chloroform showed to be the most
selective in removing the copper cations, and hence was considered
throughout the experimental study.
The effects of operating parameters such as the initial concentration
of the extracting agent, the agitation time, the agitation speed and the
acid concentration were considered.
For an initial concentration of Cu (II) of 63 ppm in a 0.5 M sulphuric
acid solution, both with a mass of the extracting agent of 20 mg, an
extraction percentage of about 97.8 % and a distribution coefficient
of 44.42 were obtained, respectively, confirming the performance
of the SDDT-Chloroform pair.
Abstract: The hydro-mechanical model for unsaturated soils has
been presented based on the effective stress principle taking into
account effects of drying-wetting process. The elasto-plastic
constitutive equations for stress-strain relations of the soil skeleton
have been established. A plasticity model is modified from modified
Cam-Clay model. The hardening rule has been established by
considering the isotropic consolidation paths. The effect of dryingwetting
process is introduced through the ¤ç parameter. All model
coefficients are identified in terms of measurable parameters. The
simulations from the proposed model are compared with the
experimental results. The model calibration was performed to extract
the model parameter from the experimental results. Good agreement
between the results predicted using proposed model and the
experimental results was obtained.
Abstract: Artemia is one of the most conspicuous invertebrates
associated with aquaculture. It can be considered as a model
organism, offering numerous advantages for comprehensive and
multidisciplinary studies using morphologic or molecular methods.
Since DNA extraction is an important step of any molecular
experiment, a new and a rapid method of DNA extraction from adult
Artemia was described in this study. Besides, the efficiency of this
technique was compared with two widely used alternative techniques,
namely Chelex® 100 resin and SDS-chloroform methods. Data
analysis revealed that the new method is the easiest and the most cost
effective method among the other methods which allows a quick and
efficient extraction of DNA from the adult animal.
Abstract: Attempts to add fibre and polyphenols (PPs) into
popular beverages present challenges related to the properties of
finished products such as smoothies. Consumer acceptability,
viscosity and phenolic composition of smoothies containing high
levels of fruit fibre (2.5-7.5 g per 300 mL serve) and PPs (250-750
mg per 300 mL serve) were examined. The changes in total
extractable PP, vitamin C content, and colour of selected smoothies
over a storage stability trial (4°C, 14 days) were compared. A set of
acidic aqueous model beverages were prepared to further examine
the effect of two different heat treatments on the stability and
extractability of PPs. Results show that overall consumer
acceptability of high fibre and PP smoothies was low, with average
hedonic scores ranging from 3.9 to 6.4 (on a 1-9 scale). Flavour,
texture and overall acceptability decreased as fibre and polyphenol
contents increased, with fibre content exerting a stronger effect.
Higher fibre content resulted in greater viscosity, with an elevated PP
content increasing viscosity only slightly. The presence of fibre also
aided the stability and extractability of PPs after heating. A reduction
of extractable PPs, vitamin C content and colour intensity of
smoothies was observed after a 14-day storage period at 4°C. Two
heat treatments (75°C for 45 min or 85°C for 1 min) that are
normally used for beverage production, did not cause significant
reduction of total extracted PPs. It is clear that high levels of added
fibre and PPs greatly influence the consumer appeal of smoothies,
suggesting the need to develop novel formulation and processing
methods if a satisfactory functional beverage is to be developed
incorporating these ingredients.
Abstract: Erwinia carotovora var. carotovora is the main cause of soft rot in potatoes. Hyphaene thebaica was studied for biocontrol of E. carotovora which inhibited growth of E. carotovora on solid medium, a comparative study of classical and ultrasound-assisted extractions of Hyphaene thebaica fruit. The use of ultrasound decreased significant the total time of treatment and increase the total amount of crude extract. The crude extract was subjected to determine the in vitro, by a bioassay technique revealed that the treatment of paper disks with ultrasound extraction of Hyphaene thebaica reduced the growth of pathogen and produced inhibition zones up to 38mm in diameter. The antioxidant activity of ultrasound-ethanolic extract of Doum fruits (Hyphaene thebaica) was determined. Data obtained showed that the extract contains the secondary metabolites such as Tannins, Saponin, Flavonoids, Phenols, Steroids, Terpenoids, Glycosides and Alkaloids.
Abstract: Application of synthetic antioxidants such as tertbutylhydroquinon
(TBHQ), in spite of their efficiency, is questioned
because of their possible carcinogenic effect. The purpose of this
study was application of mixtures of natural antioxidants that provide
the best oxidative stability for margarine. Antioxidant treatments
included 10 various mixtures (F1- F10) containing 100-500ppm
tocopherol mixture (Toc), 100-200ppm ascorbyl palmitate (AP), 100-
200ppm rosemary extract (Ros) and 1000ppm lecithin(Lec) along
with a control or F0 (with no antioxidant) and F11 with 120ppm
TBHQ. The effect of antioxidant mixtures on the stability of
margarine samples during oven test (60°C), rancimat test at 110°C
and storage at 4°C was evaluated. Final ranking of natural antioxidant
mixtures was as follows: F2,F10>F5,F9>F8>F1,F3,F4>F6, F7.
Considering the results of this research and ranking criteria,
F2(200ppmAp + 200ppmRos) and F10(200ppmRos + 200ppmToc
+1000ppmLec) were recommended as substitutes for TBHQ to
maintain the quality and increase the shelf-life of margarine.
Abstract: Construction of portable device for fast analysis of energetic materials is described in this paper. The developed analytical system consists of two main parts: a miniaturized microcolumn liquid chromatograph of unique construction and original chemiluminescence detector. This novel portable device is able to determine selectively most of nitramine- and nitroester-based explosives as well as inorganic nitrates at trace concentrations in water or soil extracts in less than 8 minutes.
Abstract: This paper presents ageing experiments controlled by the evolution of junction parameters. The deterioration of the device is related to high injection effects which modified the transport mechanisms in the space charge region of the junction. Physical phenomena linked to the degradation of junction parameters that affect the devices reliability are reported and discussed. We have used the method based on numerical analysis of experimental current-voltage characteristic of the junction, in order to extract the electrical parameters. The simultaneous follow-up of the evolutions of the series resistance and of the transition voltage allow us to introduce a new parameter for reliability evaluation.
Abstract: We proposed a technique to identify road traffic
congestion levels from velocity of mobile sensors with high accuracy
and consistent with motorists- judgments. The data collection utilized
a GPS device, a webcam, and an opinion survey. Human perceptions
were used to rate the traffic congestion levels into three levels: light,
heavy, and jam. Then the ratings and velocity were fed into a
decision tree learning model (J48). We successfully extracted vehicle
movement patterns to feed into the learning model using a sliding
windows technique. The parameters capturing the vehicle moving
patterns and the windows size were heuristically optimized. The
model achieved accuracy as high as 99.68%. By implementing the
model on the existing traffic report systems, the reports will cover
comprehensive areas. The proposed method can be applied to any
parts of the world.
Abstract: This paper describes text mining technique for automatically extracting association rules from collections of textual documents. The technique called, Extracting Association Rules from Text (EART). It depends on keyword features for discover association rules amongst keywords labeling the documents. In this work, the EART system ignores the order in which the words occur, but instead focusing on the words and their statistical distributions in documents. The main contributions of the technique are that it integrates XML technology with Information Retrieval scheme (TFIDF) (for keyword/feature selection that automatically selects the most discriminative keywords for use in association rules generation) and use Data Mining technique for association rules discovery. It consists of three phases: Text Preprocessing phase (transformation, filtration, stemming and indexing of the documents), Association Rule Mining (ARM) phase (applying our designed algorithm for Generating Association Rules based on Weighting scheme GARW) and Visualization phase (visualization of results). Experiments applied on WebPages news documents related to the outbreak of the bird flu disease. The extracted association rules contain important features and describe the informative news included in the documents collection. The performance of the EART system compared with another system that uses the Apriori algorithm throughout the execution time and evaluating extracted association rules.
Abstract: An important step in studying the statistics of
fingerprint minutia features is to reliably extract minutia features from
the fingerprint images. A new reliable method of computation for
minutiae feature extraction from fingerprint images is presented. A
fingerprint image is treated as a textured image. An orientation flow
field of the ridges is computed for the fingerprint image. To
accurately locate ridges, a new ridge orientation based computation
method is proposed. After ridge segmentation a new method of
computation is proposed for smoothing the ridges. The ridge skeleton
image is obtained and then smoothed using morphological operators
to detect the features. A post processing stage eliminates a large
number of false features from the detected set of minutiae features.
The detected features are observed to be reliable and accurate.
Abstract: We present a new method for the fully automatic 3D
reconstruction of the coronary artery centerlines, using two X-ray
angiogram projection images from a single rotating monoplane
acquisition system. During the first stage, the input images are
smoothed using curve evolution techniques. Next, a simple yet
efficient multiscale method, based on the information of the Hessian
matrix, for the enhancement of the vascular structure is introduced.
Hysteresis thresholding using different image quantiles, is used to
threshold the arteries. This stage is followed by a thinning procedure
to extract the centerlines. The resulting skeleton image is then pruned
using morphological and pattern recognition techniques to remove
non-vessel like structures. Finally, edge-based stereo correspondence
is solved using a parallel evolutionary optimization method based on
f symbiosis. The detected 2D centerlines combined with disparity
map information allow the reconstruction of the 3D vessel
centerlines. The proposed method has been evaluated on patient data
sets for evaluation purposes.
Abstract: A filter is used to remove undesirable frequency information from a dynamic signal. This paper shows that the Znotch filter filtering technique can be applied to remove the noise nuisance from a machining signal. In machining, the noise components were identified from the sound produced by the operation of machine components itself such as hydraulic system, motor, machine environment and etc. By correlating the noise components with the measured machining signal, the interested components of the measured machining signal which was less interfered by the noise, can be extracted. Thus, the filtered signal is more reliable to be analysed in terms of noise content compared to the unfiltered signal. Significantly, the I-kaz method i.e. comprises of three dimensional graphical representation and I-kaz coefficient, Z∞ could differentiate between the filtered and the unfiltered signal. The bigger space of scattering and the higher value of Z∞ demonstrated that the signal was highly interrupted by noise. This method can be utilised as a proactive tool in evaluating the noise content in a signal. The evaluation of noise content is very important as well as the elimination especially for machining operation fault diagnosis purpose. The Z-notch filtering technique was reliable in extracting noise component from the measured machining signal with high efficiency. Even though the measured signal was exposed to high noise disruption, the signal generated from the interaction between cutting tool and work piece still can be acquired. Therefore, the interruption of noise that could change the original signal feature and consequently can deteriorate the useful sensory information can be eliminated.
Abstract: A human verification system is presented in this
paper. The system consists of several steps: background subtraction,
thresholding, line connection, region growing, morphlogy, star
skelatonization, feature extraction, feature matching, and decision
making. The proposed system combines an advantage of star
skeletonization and simple statistic features. A correlation matching
and probability voting have been used for verification, followed by a
logical operation in a decision making stage. The proposed system
uses small number of features and the system reliability is
convincing.
Abstract: This paper presents a useful sub-pixel image
registration method using line segments and a sub-pixel edge detector.
In this approach, straight line segments are first extracted from gray
images at the pixel level before applying the sub-pixel edge detector.
Next, all sub-pixel line edges are mapped onto the orientation-distance
parameter space to solve for line correspondence between images.
Finally, the registration parameters with sub-pixel accuracy are
analytically solved via two linear least-square problems. The present
approach can be applied to various fields where fast registration with
sub-pixel accuracy is required. To illustrate, the present approach is
applied to the inspection of printed circuits on a flat panel. Numerical
example shows that the present approach is effective and accurate
when target images contain a sufficient number of line segments,
which is true in many industrial problems.