Abstract: An early and accurate detection of Alzheimer's disease (AD) is an important stage in the treatment of individuals suffering from AD. We present an approach based on the use of structural magnetic resonance imaging (sMRI) phase images to distinguish between normal controls (NC), mild cognitive impairment (MCI) and AD patients with clinical dementia rating (CDR) of 1. Independent component analysis (ICA) technique is used for extracting useful features which form the inputs to the support vector machines (SVM), K nearest neighbour (kNN) and multilayer artificial neural network (ANN) classifiers to discriminate between the three classes. The obtained results are encouraging in terms of classification accuracy and effectively ascertain the usefulness of phase images for the classification of different stages of Alzheimer-s disease.
Abstract: In this paper a Pattern Recognition algorithm based on
a constrained version of the k-means clustering algorithm will be
presented. The proposed algorithm is a non parametric supervised
statistical pattern recognition algorithm, i.e. it works under very mild
assumptions on the dataset. The performance of the algorithm will
be tested, togheter with a feature extraction technique that captures
the information on the closed two-dimensional contour of an image,
on images of industrial mineral ores.
Abstract: A new approach is adopted in this paper based
on Turk and Pentland-s eigenface method. It was found that the
probability density function of the distance between the projection
vector of the input face image and the average projection vector of
the subject in the face database, follows Rayleigh distribution. In
order to decrease the false acceptance rate and increase the
recognition rate, the input face image has been recognized using two
thresholds including the acceptance threshold and the rejection
threshold. We also find out that the value of two thresholds will be
close to each other as number of trials increases. During the training,
in order to reduce the number of trials, the projection vectors for each
subject has been averaged. The recognition experiments using the
proposed algorithm show that the recognition rate achieves to
92.875% whilst the average number of judgment is only 2.56 times.
Abstract: In this paper, we present symbolic recognition models to extract knowledge characterized by document structures. Focussing on the extraction and the meticulous exploitation of the semantic structure of documents, we obtain a meaningful contextual tagging corresponding to different unit types (title, chapter, section, enumeration, etc.).
Abstract: Scale Invariant Feature Transform (SIFT) has been
widely applied, but extracting SIFT feature is complicated and
time-consuming. In this paper, to meet the demand of the real-time
applications, SIFT is parallelized and optimized on cluster system,
which is named pSIFT. Redundancy storage and communication are
used for boundary data to improve the performance, and before
representation of feature descriptor, data reallocation is adopted to
keep load balance in pSIFT. Experimental results show that pSIFT
achieves good speedup and scalability.
Abstract: People detection from images has a variety of applications such as video surveillance and driver assistance system, but is still a challenging task and more difficult in crowded environments such as shopping malls in which occlusion of lower parts of human body often occurs. Lack of the full-body information requires more effective features than common features such as HOG. In this paper, new features are introduced that exploits global self-symmetry (GSS) characteristic in head-shoulder patterns. The features encode the similarity or difference of color histograms and oriented gradient histograms between two vertically symmetric blocks. The domain-specific features are rapid to compute from the integral images in Viola-Jones cascade-of-rejecters framework. The proposed features are evaluated with our own head-shoulder dataset that, in part, consists of a well-known INRIA pedestrian dataset. Experimental results show that the GSS features are effective in reduction of false alarmsmarginally and the gradient GSS features are preferred more often than the color GSS ones in the feature selection.
Abstract: Impurity metals such as manganese and cadmium
from high-tenor cobalt electrolyte solution were selectively removed
by solvent extraction method using Co-D2EHPA after converting the functional group of D2EHPA with Co2+ ions. The process parameters
such as pH, organic concentration, O/A ratio, kinetics etc. were
investigated and the experiments were conducted by batch tests in the laboratory bench scale. Results showed that a significant amount
of manganese and cadmium can be extracted using Co-D2EHPA for the optimum processing of cobalt electrolyte solution at equilibrium pH about 3.5. The McCabe-Thiele diagram, constructed from the
extraction studies showed that 100% impurities can be extracted through four stages for manganese and three stages for cadmium
using O/A ratio of 0.65 and 1.0, respectively. From the stripping study, it was found that 100% manganese and cadmium can be stripped from the loaded organic using 0.4 M H2SO4 in a single
contact. The loading capacity of Co-D2EHPA by manganese and cadmium were also investigated with different O/A ratio as well as
with number of stages of contact of aqueous and organic phases. Valuable information was obtained for the designing of an impurities
removal process for the production of pure cobalt with less trouble in the electrowinning circuit.
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: In non destructive testing by radiography, a perfect
knowledge of the weld defect shape is an essential step to
appreciate the quality of the weld and make decision on its
acceptability or rejection. Because of the complex nature of the
considered images, and in order that the detected defect region
represents the most accurately possible the real defect, the choice
of thresholding methods must be done judiciously. In this paper,
performance criteria are used to conduct a comparative study of
four non parametric histogram thresholding methods for automatic
extraction of weld defect in radiographic images.
Abstract: The in vitro culture procedure of purple nutsedge
(Cyperus rotundus L.) for multiple shoot induction and tuber
formation was established. Multiple shoots were significantly
induced from a single shoot of about 0.5 – 0.8 cm long, on Murashige
and Skoog (MS) medium supplemented with 4.44 μM 6-
benzyladinine (BA) alone or in combination with 2.85 μM 1-
indoleacetic acid (IAA), providing 17.6 and 15.3 shoots per explant
with 31.2 and 27.5 leaves per explant, respectively, within 6 weeks of
culturing. Moreover, MS medium supplemented with 4.44 μM BA
and 2.85 μM IAA was suitable for tuber induction, obtaining 5.9
tubers with 3.4 rhizomes per explant. In combination with ancymidol
and higher concentration of sucrose, 11.1 μM BA and 60 g/L sucrose
or 11.1 μM BA, 7.8 μM ancymidol and 60 g/L sucrose induced 3.5
tubers with 1.6 rhizomes or 3.5 tubers without rhizome, respectively.
However, MS medium containing 3.9 or 7.8 μM ancymidol in
combination with either 60 or 80 g/L sucrose enchanced significant
root formation at 20.9 – 23.6 roots per explant.
Abstract: Ice cover County has a significant impact on rivers as it affects with the ice melting capacity which results in flooding, restrict navigation, modify the ecosystem and microclimate. River ices are made up of different ice types with varying ice thickness, so surveillance of river ice plays an important role. River ice types are captured using infrared imaging camera which captures the images even during the night times. In this paper the river ice infrared texture images are analysed using first-order statistical methods and secondorder statistical methods. The second order statistical methods considered are spatial gray level dependence method, gray level run length method and gray level difference method. The performance of the feature extraction methods are evaluated by using Probabilistic Neural Network classifier and it is found that the first-order statistical method and second-order statistical method yields low accuracy. So the features extracted from the first-order statistical method and second-order statistical method are combined and it is observed that the result of these combined features (First order statistical method + gray level run length method) provides higher accuracy when compared with the features from the first-order statistical method and second-order statistical method alone.
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.
Abstract: In this paper, a novel road extraction method using Stationary Wavelet Transform is proposed. To detect road features from color aerial satellite imagery, Mexican hat Wavelet filters are used by applying the Stationary Wavelet Transform in a multiresolution, multi-scale, sense and forming the products of Wavelet coefficients at a different scales to locate and identify road features at a few scales. In addition, the shifting of road features locations is considered through multiple scales for robust road extraction in the asymmetry road feature profiles. From the experimental results, the proposed method leads to a useful technique to form the basis of road feature extraction. Also, the method is general and can be applied to other features in imagery.
Abstract: The industrial process of the sugar cane crystallization produces a residual that still contains a lot of soluble sucrose and the objective of the factory is to improve its extraction. Therefore, there are substantial losses justifying the search for the optimization of the process. Crystallization process studied on the industrial site is based on the “three massecuites process". The third step of this process constitutes the final stage of exhaustion of the sucrose dissolved in the mother liquor. During the process of the third step of crystallization (Ccrystallization), the phase that is studied and whose control is to be improved, is the growing phase (crystal growth phase). The study of this process on the industrial site is a problem in its own. A control scheme is proposed to improve the standard PID control law used in the factory. An auto-tuning PID controller based on instantaneous linearization of a neural network is then proposed.
Abstract: Recently ORC(Organic Rankine Cycle) has attracted
much attention due to its potential in reducing consumption of fossil
fuels and its favorable characteristics to exploit low-grade heat sources.
In this work thermodynamic performance of ORC with superheating of
vapor is comparatively assessed for various working fluids. Special
attention is paid to the effects of system parameters such as the evaporating
temperature and the turbine inlet temperature on the characteristics
of the system such as maximum possible work extraction from
the given source, volumetric flow rate per 1 kW of net work and
quality of the working fluid at turbine exit as well as thermal and
exergy efficiencies. Results show that for a given source the thermal
efficiency increases with decrease of the superheating but exergy
efficiency may have a maximum value with respect to the superheating
of the working fluid. Results also show that in selection of working
fluid it is required to consider various criteria of performance characteristics
as well as thermal efficiency.
Abstract: Using strength Pulse Electrical Field (PEF) in food
industries is a non-thermal process that can deactivate
microorganisms and increase penetration in plant and animals tissues
without serious impact on food taste and quality. In this paper designing and fabricating of a PEF generator has been presented. Pulse generation methods have been surveyed and the best of them
selected. The equipment by controller set can generate square pulse with adjustable parameters such as amplitude 1-5kV, frequency 0.1-10Hz, pulse width 10-100s, and duty cycle 0-100%. Setting the number of pulses, and presenting the output voltage and current
waveforms on the oscilloscope screen are another advantages of this
equipment. Finally, some food samples were tested that yielded the satisfactory results. PEF applying had considerable effects on potato, banana and purple cabbage. It caused increase Brix factor from 0.05
to 0.15 in potato solution. It is also so effective in extraction color material from purple cabbage. In the last experiment effects of PEF
voltages on color extraction of saffron scum were surveyed (about 6% increasing yield).
Abstract: Antifungal activities of ether and methanolic extracts of volatiles oils of Nigella Sativa seeds were tested against pathogenic bacterias and fungies strains.The volatile oil were found to have significant antifungal and antibacterial activities compare to tetracycline, cefuroxime and ciprofloxacin positive controls.The ether and methanolic esxtracts were compared to each other for antifungal and antibacterial activities and ether extracts showed stonger activity than methanolic one.
Abstract: Phytophthora cinnamomi (P. c) is a plant pathogenic
oomycete that is capable of damaging plants in commercial production
systems and natural ecosystems worldwide. The most common
methods for the detection and diagnosis of P. c infection are
expensive, elaborate and time consuming. This study was carried out
to examine whether species specific and life cycle specific volatile
organic compounds (VOCs) can be absorbed by solid-phase
microextraction fibers and detected by gas chromatography that are
produced by P. c and another oomycete Pythium dissotocum. A
headspace solid-phase microextraction (HS-SPME) together with gas
chromatography (GC) method was developed and optimized for the
identification of the VOCs released by P. c. The optimized parameters
included type of fiber, exposure time, desorption temperature and
desorption time. Optimization was achieved with the analytes of P.
c+V8A and V8A alone. To perform the HS-SPME, six types of fiber
were assayed and compared: 7μm Polydimethylsiloxane (PDMS),
100μm Polydimethylsiloxane (PDMS), 50/30μm
Divinylbenzene/CarboxenTM/Polydimethylsiloxane
DVB/CAR/PDMS), 65μm Polydimethylsiloxane/Divinylbenzene
(PDMS/DVB), 85μm Polyacrylate (PA) fibre and 85μm CarboxenTM/
Polydimethylsiloxane (Carboxen™/PDMS). In a comparison of the
efficacy of the fibers, the bipolar fiber DVB/CAR/PDMS had a higher
extraction efficiency than the other fibers. An exposure time of 16h
with DVB/CAR/PDMS fiber in the sample headspace was enough to
reach the maximum extraction efficiency. A desorption time of 3min
in the GC injector with the desorption temperature of 250°C was
enough for the fiber to desorb the compounds of interest. The chromatograms and morphology study confirmed that the VOCs from
P. c+V8A had distinct differences from V8A alone, as did different
life cycle stages of P. c and different taxa such as Pythium dissotocum.
The study proved that P. c has species and life cycle specific VOCs,
which in turn demonstrated the feasibility of this method as means of
Abstract: Iris-based biometric authentication is gaining importance
in recent times. Iris biometric processing however, is a complex
process and computationally very expensive. In the overall processing
of iris biometric in an iris-based biometric authentication system,
feature processing is an important task. In feature processing, we extract
iris features, which are ultimately used in matching. Since there
is a large number of iris features and computational time increases
as the number of features increases, it is therefore a challenge to
develop an iris processing system with as few as possible number of
features and at the same time without compromising the correctness.
In this paper, we address this issue and present an approach to feature
extraction and feature matching process. We apply Daubechies D4
wavelet with 4 levels to extract features from iris images. These
features are encoded with 2 bits by quantizing into 4 quantization
levels. With our proposed approach it is possible to represent an
iris template with only 304 bits, whereas existing approaches require
as many as 1024 bits. In addition, we assign different weights to
different iris region to compare two iris templates which significantly
increases the accuracy. Further, we match the iris template based on
a weighted similarity measure. Experimental results on several iris
databases substantiate the efficacy of our approach.
Abstract: In this study, a novel approach of image embedding is introduced. The proposed method consists of three main steps. First, the edge of the image is detected using Sobel mask filters. Second, the least significant bit LSB of each pixel is used. Finally, a gray level connectivity is applied using a fuzzy approach and the ASCII code is used for information hiding. The prior bit of the LSB represents the edged image after gray level connectivity, and the remaining six bits represent the original image with very little difference in contrast. The proposed method embeds three images in one image and includes, as a special case of data embedding, information hiding, identifying and authenticating text embedded within the digital images. Image embedding method is considered to be one of the good compression methods, in terms of reserving memory space. Moreover, information hiding within digital image can be used for security information transfer. The creation and extraction of three embedded images, and hiding text information is discussed and illustrated, in the following sections.