Abstract: Tamil handwritten document is taken as a key source of data to identify the writer. Tamil is a classical language which has 247 characters include compound characters, consonants, vowels and special character. Most characters of Tamil are multifaceted in nature. Handwriting is a unique feature of an individual. Writer may change their handwritings according to their frame of mind and this place a risky challenge in identifying the writer. A new discriminative model with pooled features of handwriting is proposed and implemented using support vector machine. It has been reported on 100% of prediction accuracy by RBF and polynomial kernel based classification model.
Abstract: The influence of cultivation factors such as content of ammonium sulfate, glucose and water in the culture medium and particle size of dry orange waste, on their bioconversion for pectinase production was studied using complete factorial design. A polygalacturonase (PG) was isolated using ion exchange chromatography under gradient elution 0-0,5 m/l NaCl (column equilibrate with acetate buffer pH 4,5), subsequently by sephadex G75 column chromatography was applied and the molecular weight was obtained about 51,28 KDa. Purified PG enzyme exhibits a pH and temperature optima of activity at 5 and 35°C respectively. Treatment of apple juice by purified enzyme extract yielded a clear juice, which was competitive with juice yielded by pure Sigma Aldrich Aspergillus niger enzyme.
Abstract: Web mining is to discover and extract useful
Information. Different users may have different search goals when
they search by giving queries and submitting it to a search engine.
The inference and analysis of user search goals can be very useful for
providing an experience result for a user search query. In this project,
we propose a novel approach to infer user search goals by analyzing
search web logs. First, we propose a novel approach to infer user
search goals by analyzing search engine query logs, the feedback
sessions are constructed from user click-through logs and it
efficiently reflect the information needed for users. Second we
propose a preprocessing technique to clean the unnecessary data’s
from web log file (feedback session). Third we propose a technique
to generate pseudo-documents to representation of feedback sessions
for clustering. Finally we implement k-medoids clustering algorithm
to discover different user search goals and to provide a more optimal
result for a search query based on feedback sessions for the user.
Abstract: The present study aims to investigate the performance
of Moringa oleifera seed extract as natural coagulant in clarification
of secondary wastewater treatment plant (MWWTP) located in East
of Algiers, Algeria. Coagulation flocculation performance of
Moringa oleifera was evaluated through supernatant residual
turbidity after jar test trials. Various influence parameters namely
Moringa oleifera dosage and pH have been considered. Tests on
Reghaia wastewater, having 129 NTU of initial turbidity, showed a
removal of 69.45% of residual turbidity with only 1.5 mg/l of
Moringa oleifera. This sufficient removal capability encourages the
use of this bioflocculant for treatment of turbid waters. Indeed,
Moringa oleifera which is a natural resource available locally (South
of Algeria) coupled to the non-toxicity, biocompatibility and
biodegradability, may be a very interesting alternative to the
conventional coagulants used so far.
Abstract: Natural dyes are gaining interest due their expected
low risk to human health and to the environment. In this study, the
wash fastness of a natural coloring matter from the liquid waste
produced in the steam treatment of eucalyptus wood in textile fabrics
was investigated. Specifically, eucalyptus wood extract was used to
dye cotton, nylon and wool in an exhaust dyeing process without the
addition of the traditional mordanting agents and then submitted to
wash fastness analysis. The resulting dyed fabrics were evaluated for
color fastness. It was found that wash fastness of dyed fabrics was
very good to cotton and excellent to nylon and wool.
Abstract: This paper presents the influences on the entrainment
of serpentines by grinding and reagents during copper–nickel sulfide
flotation. The previous bench flotation tests were performed to extract
the metallic values from the ore in Yunnan Mine, China and the
relatively satisfied results with recoveries of 86.92% Cu, 54.92% Ni,
and 74.73% Pt+Pd in the concentrate were harvested at their grades of
4.02%, 3.24% and 76.61 g/t, respectively. However, the content of
MgO in the concentrate was still more than 19%. Micro-flotation tests
were conducted with the objective of figuring out the influences on the
entrainment of serpentines into the concentrate by particle size,
flocculants or depressants and collectors, as well as visual
observations in suspension by OLYMPUS camera. All the tests results
pointed to the presences of both “entrapped-in” serpentines and its
coating on the hydrophobic flocs resulted from strong collectors
(combination of butyl xanthate, butyl ammonium dithophosphate,
even after adding carboxymethyl cellulose as effective depressant.
And fine grinding may escalate the entrainment of serpentines in the
concentrate.
Abstract: The present work is aimed at examining carbon steel
oil pipelines corrosion using three natural extracts (Eruca Sativa,
Rosell and Mango peels) that are used as inhibitors of different
concentrations ranging from 0.05-0.1wt. %. Two sulphur compounds
are used as corrosion mediums. Weight loss method was used for
measuring the corrosion rate of the carbon steel specimens immersed
in technical white oil at 100ºC at various time intervals in absence
and presence of the two sulphur compounds. The corroded specimens
are examined using the chemical wear test, scratch test and hardness
test. The scratch test is carried out using scratch loads from 0.5 Kg to
2.0 Kg. The scratch width is obtained at various scratch load and test
conditions. The Brinell hardness test is carried out and investigated
for both corroded and inhibited specimens. The results showed that
three natural extracts can be used as environmentally friendly
corrosion inhibitors.
Abstract: Consumers are demanding novel beverages that are
healthier, convenient and have appealing consumer acceptance. The
objectives of this study were to investigate the effects of adding grape
polyphenols and the influence of presenting health claims on the
sensory acceptability of wines. Fresh red sorrel calyces were
fermented into wines. The total soluble solids of the pectinase-treated
sorrel puree were from 4°Brix to 23.8°Brix. Polyphenol in the form
of grape pomace extract was added to sorrel wines (w/v) in specified
levels to give 0. 25. 50 and 75 ppm. A focus group comprising of 12
panelists was use to select the level of polyphenol to be added to
sorrel wines for sensory preference The sensory attributed of the
wines which were evaluated were colour, clarity, aroma, flavor,
mouth-feel, sweetness, astringency and overall preference. The sorrel
wine which was most preferred from focus group evaluation was
presented for hedonic rating. In the first stage of hedonic testing, the
sorrel wine was served chilled at 7°C for 24 h prior to sensory
evaluation. Each panelist was provided with a questionnaire and was
asked to rate the wines on colour, aroma, flavor, mouth-feel,
sweetness, astringency and overall acceptability using a 9-point
hedonic scale. In the second stage of hedonic testing, the panelist
were instructed to read a health abstract on the health benefits of
polyphenolic compounds and again to rate sorrel wine with added 25
ppm polyphenol. Paired t-test was used for the analysis of the
influence of presenting health information on polyphenols on hedonic
scoring of sorrel wines. Focus groups found that the addition of
polyphenol addition had no significant effect on sensory color and
aroma but affected clarity and flavor. A 25 ppm wine was liked
moderately in overall acceptability. The presentation of information
on the health benefit of polyphenols in sorrel wines to panelists had
no significant influence on the sensory acceptance of wine. More
than half of panelists would drink this wine now and then. This wine
had color L 19.86±0.68, chroma 2.10±0.12, hue° 16.90 ±3.10 and
alcohol content of 13.0%. The sorrel wine was liked moderately in
overall acceptability with the added polyphenols.
Abstract: Computer aided diagnosis systems provide vital
opinion to radiologists in the detection of early signs of breast cancer
from mammogram images. Architectural distortions, masses and
microcalcifications are the major abnormalities. In this paper, a
computer aided diagnosis system has been proposed for
distinguishing abnormal mammograms with architectural distortion
from normal mammogram. Four types of texture features GLCM
texture, GLRLM texture, fractal texture and spectral texture features
for the regions of suspicion are extracted. Support vector machine
has been used as classifier in this study. The proposed system yielded
an overall sensitivity of 96.47% and an accuracy of 96% for
mammogram images collected from digital database for screening
mammography database.
Abstract: In this paper, we present a new segmentation approach
for focal liver lesions in contrast enhanced ultrasound imaging. This
approach, based on a two-cluster Fuzzy C-Means methodology,
considers type-II fuzzy sets to handle uncertainty due to the image
modality (presence of speckle noise, low contrast, etc.), and to
calculate the optimum inter-cluster threshold. Fine boundaries are
detected by a local recursive merging of ambiguous pixels. The
method has been tested on a representative database. Compared to
both Otsu and type-I Fuzzy C-Means techniques, the proposed
method significantly reduces the segmentation errors.
Abstract: Sewer deposits have been identified as a major cause
of dysfunctions in combined sewer systems regarding sewer
management, which induces different negative consequents resulting
in poor hydraulic conveyance, environmental damages as well as
worker’s health. In order to overcome the problematics of
sedimentation, flushing has been considered as the most operative
and cost-effective way to minimize the sediments impacts and
prevent such challenges. Flushing, by prompting turbulent wave
effects, can modify the bed form depending on the hydraulic
properties and geometrical characteristics of the conduit. So far, the
dynamics of the bed-load during high-flow events in combined sewer
systems as a complex environment is not well understood, mostly due
to lack of measuring devices capable to work in the “hostile” in
combined sewer system correctly. In this regards, a one-episode
flushing issue from an opening gate valve with weir function was
carried out in a trunk sewer in Paris to understand its cleansing
efficiency on the sediments (thickness: 0-30 cm). During more than
1h of flushing within 5 m distance in downstream of this flushing
device, a maximum flowrate and a maximum level of water have
been recorded at 5 m in downstream of the gate as 4.1 m3/s and 2.1
m respectively. This paper is aimed to evaluate the efficiency of this
type of gate for around 1.1 km (from the point -50 m to +1050 m in
downstream from the gate) by (i) determining bed grain-size
distribution and sediments evolution through the sewer channel, as
well as their organic matter content, and (ii) identifying sections that
exhibit more changes in their texture after the flush. For the first one,
two series of sampling were taken from the sewer length and then
analyzed in laboratory, one before flushing and second after, at same
points among the sewer channel. Hence, a non-intrusive sampling
instrument has undertaken to extract the sediments smaller than the
fine gravels. The comparison between sediments texture after the
flush operation and the initial state, revealed the most modified zones
by the flush effect, regarding the sewer invert slope and hydraulic
parameters in the zone up to 400 m from the gate. At this distance,
despite the increase of sediment grain-size rages, D50 (median grainsize)
varies between 0.6 mm and 1.1 mm compared to 0.8 mm and 10
mm before and after flushing, respectively. Overall, regarding the
sewer channel invert slope, results indicate that grains smaller than
sands (< 2 mm) are more transported to downstream along about 400
m from the gate: in average 69% before against 38% after the flush
with more dispersion of grain-sizes distributions. Furthermore, high
effect of the channel bed irregularities on the bed material evolution
has been observed after the flush.
Abstract: One of the most critical decision points in the design of a
face recognition system is the choice of an appropriate face representation.
Effective feature descriptors are expected to convey sufficient, invariant
and non-redundant facial information. In this work we propose a set of
Hahn moments as a new approach for feature description. Hahn moments
have been widely used in image analysis due to their invariance, nonredundancy
and the ability to extract features either globally and locally.
To assess the applicability of Hahn moments to Face Recognition we
conduct two experiments on the Olivetti Research Laboratory (ORL)
database and University of Notre-Dame (UND) X1 biometric collection.
Fusion of the global features along with the features from local facial
regions are used as an input for the conventional k-NN classifier. The
method reaches an accuracy of 93% of correctly recognized subjects for
the ORL database and 94% for the UND database.
Abstract: The disposal and the treatment of sewage sludge is an
expensive and environmentally complex problem. In this work, a
lipopeptide biosurfactant extracted from corn steep liquor was used
as ecofriendly and cost-competitive alternative for the mobilization
and bioremediation of fluorene in sewage sludge. Results have
demonstrated that this biosurfactant has the capability to mobilize
fluorene to the aqueous phase, reducing the amount of fluorene in the
sewage sludge from 484.4 mg/Kg up to 413.7 mg/Kg and 196.0
mg/Kg after 1 and 27 days respectively. Furthermore, once the
fluorene was extracted the lipopeptide biosurfactant contained in the
aqueous phase allowed the biodegradation, up to 40.5% of the initial
concentration of this polycyclic aromatic hydrocarbon.
Abstract: Speaker Identification (SI) is the task of establishing
identity of an individual based on his/her voice characteristics. The SI
task is typically achieved by two-stage signal processing: training and
testing. The training process calculates speaker specific feature
parameters from the speech and generates speaker models
accordingly. In the testing phase, speech samples from unknown
speakers are compared with the models and classified. Even though
performance of speaker identification systems has improved due to
recent advances in speech processing techniques, there is still need of
improvement. In this paper, a Closed-Set Tex-Independent Speaker
Identification System (CISI) based on a Multiple Classifier System
(MCS) is proposed, using Mel Frequency Cepstrum Coefficient
(MFCC) as feature extraction and suitable combination of vector
quantization (VQ) and Gaussian Mixture Model (GMM) together
with Expectation Maximization algorithm (EM) for speaker
modeling. The use of Voice Activity Detector (VAD) with a hybrid
approach based on Short Time Energy (STE) and Statistical
Modeling of Background Noise in the pre-processing step of the
feature extraction yields a better and more robust automatic speaker
identification system. Also investigation of Linde-Buzo-Gray (LBG)
clustering algorithm for initialization of GMM, for estimating the
underlying parameters, in the EM step improved the convergence rate
and systems performance. It also uses relative index as confidence
measures in case of contradiction in identification process by GMM
and VQ as well. Simulation results carried out on voxforge.org
speech database using MATLAB highlight the efficacy of the
proposed method compared to earlier work.
Abstract: This research presents the main ideas to implement an
intelligent system composed by communicating wireless sensors
measuring environmental data linked to drought indicators (such as
air temperature, soil moisture , etc...). On the other hand, the setting
up of a spatio temporal database communicating with a Web mapping
application for a monitoring in real time in activity 24:00 /day, 7
days/week is proposed to allow the screening of the drought
parameters time evolution and their extraction. Thus this system
helps detecting surfaces touched by the phenomenon of drought.
Spatio-temporal conceptual models seek to answer the users who
need to manage soil water content for irrigating or fertilizing or other
activities pursuing crop yield augmentation. Effectively, spatiotemporal
conceptual models enable users to obtain a diagram of
readable and easy data to apprehend. Based on socio-economic
information, it helps identifying people impacted by the phenomena
with the corresponding severity especially that this information is
accessible by farmers and stakeholders themselves. The study will be
applied in Siliana watershed Northern Tunisia.
Abstract: In order to help the expert to validate association rules
extracted from data, some quality measures are proposed in the
literature. We distinguish two categories: objective and subjective
measures. The first one depends on a fixed threshold and on data
quality from which the rules are extracted. The second one consists
on providing to the expert some tools in the objective to explore and
visualize rules during the evaluation step. However, the number of
extracted rules to validate remains high. Thus, the manually mining
rules task is very hard. To solve this problem, we propose, in this
paper, a semi-automatic method to assist the expert during the
association rule's validation. Our method uses rule-based
classification as follow: (i) We transform association rules into
classification rules (classifiers), (ii) We use the generated classifiers
for data classification. (iii) We visualize association rules with their
quality classification to give an idea to the expert and to assist him
during validation process.
Abstract: Particle size distribution, the most important
characteristics of aerosols, is obtained through electrical
characterization techniques. The dynamics of charged nanoparticles
under the influence of electric field in Electrical Mobility
Spectrometer (EMS) reveals the size distribution of these particles.
The accuracy of this measurement is influenced by flow conditions,
geometry, electric field and particle charging process, therefore by
the transfer function (transfer matrix) of the instrument. In this work,
a wire-cylinder corona charger was designed and the combined fielddiffusion
charging process of injected poly-disperse aerosol particles
was numerically simulated as a prerequisite for the study of a
multichannel EMS. The result, a cloud of particles with no uniform
charge distribution, was introduced to the EMS. The flow pattern and
electric field in the EMS were simulated using Computational Fluid
Dynamics (CFD) to obtain particle trajectories in the device and
therefore to calculate the reported signal by each electrometer.
According to the output signals (resulted from bombardment of
particles and transferring their charges as currents), we proposed a
modification to the size of detecting rings (which are connected to
electrometers) in order to evaluate particle size distributions more
accurately. Based on the capability of the system to transfer
information contents about size distribution of the injected particles,
we proposed a benchmark for the assessment of optimality of the
design. This method applies the concept of Von Neumann entropy
and borrows the definition of entropy from information theory
(Shannon entropy) to measure optimality. Entropy, according to the
Shannon entropy, is the ''average amount of information contained in
an event, sample or character extracted from a data stream''.
Evaluating the responses (signals) which were obtained via various
configurations of detecting rings, the best configuration which gave
the best predictions about the size distributions of injected particles,
was the modified configuration. It was also the one that had the
maximum amount of entropy. A reasonable consistency was also
observed between the accuracy of the predictions and the entropy
content of each configuration. In this method, entropy is extracted
from the transfer matrix of the instrument for each configuration.
Ultimately, various clouds of particles were introduced to the
simulations and predicted size distributions were compared to the
exact size distributions.
Abstract: Chalcopyrite (CuFeS2) is the most common primary
mineral used for the commercial production of copper. The low
dissolution efficiency of chalcopyrite in sulfate media has prevented
an efficient industrial leaching of this mineral in sulfate media. Ferric
ions, bacteria, oxygen and other oxidants have been used as oxidizing
agents in the leaching of chalcopyrite in sulfate and chloride media
under atmospheric or pressure leaching conditions. Two leaching
methods were studied to evaluate chalcopyrite (CuFeS2) dissolution
in acid media. First, the conventional oxidative acid leaching method
was carried out using sulfuric acid (H2SO4) and potassium
dichromate (K2Cr2O7) as oxidant at atmospheric pressure. Second,
microwave-assisted acid leaching was performed using the
microwave accelerated reaction system (MARS) for same reaction
media. Parameters affecting the copper extraction such as leaching
time, leaching temperature, concentration of H2SO4 and
concentration of K2Cr2O7 were investigated. The results of
conventional acid leaching experiments were compared to the
microwave leaching method. It was found that the copper extraction
obtained under high temperature and high concentrations of oxidant
with microwave leaching is higher than those obtained
conventionally. 81% copper extraction was obtained by the
conventional oxidative acid leaching method in 180 min, with the
concentration of 0.3 mol/L K2Cr2O7 in 0.5M H2SO4 at 50 ºC, while
93.5% copper extraction was obtained in 60 min with microwave
leaching method under same conditions.
Abstract: This paper presents the local mesh co-occurrence
patterns (LMCoP) using HSV color space for image retrieval system.
HSV color space is used in this method to utilize color, intensity and
brightness of images. Local mesh patterns are applied to define the
local information of image and gray level co-occurrence is used to
obtain the co-occurrence of LMeP pixels. Local mesh co-occurrence
pattern extracts the local directional information from local mesh
pattern and converts it into a well-mannered feature vector using gray
level co-occurrence matrix. The proposed method is tested on three
different databases called MIT VisTex, Corel, and STex. Also, this
algorithm is compared with existing methods, and results in terms of
precision and recall are shown in this paper.
Abstract: Phonocardiography is important in appraisal of
congenital heart disease and pulmonary hypertension as it reflects the
duration of right ventricular systoles. The systolic murmur in patients
with intra-cardiac shunt decreases as pulmonary hypertension
develops and may eventually disappear completely as the pulmonary
pressure reaches systemic level. Phonocardiography and auscultation
are non-invasive, low-cost, and accurate methods to assess heart
disease. In this work an objective signal processing tool to extract
information from phonocardiography signal using Wavelet is
proposed to classify the murmur as normal or abnormal. Since the
feature vector is large, a Binary Particle Swarm Optimization (PSO)
with mutation for feature selection is proposed. The extracted
features improve the classification accuracy and were tested across
various classifiers including Naïve Bayes, kNN, C4.5, and SVM.