Abstract: The Iranian bentonite was first characterized by
Scanning Electron Microscopy (SEM), Inductively Coupled Plasma
mass spectrometry (ICP-MS), X-ray fluorescence (XRF), X-ray
Diffraction (XRD) and BET. The bentonite was then treated
thermally between 150°C-250°C at 15min, 45min and 90min and
also was activated chemically with different concentration of
sulphuric acid (3N, 5N and 10N). Although the results of thermal
activated-bentonite didn-t show any considerable changes in specific
surface area and Cation Exchange Capacity (CEC), but the results of
chemical treated bentonite demonstrated that such properties have
been improved by acid activation process.
Abstract: A two-dimensional numerical simulation of crossflow
around four cylinders in an in-line rectangular configuration is
studied by using the lattice Boltzmann method (LBM). Special
attention is paid to the effect of the spacing between the cylinders.
The Reynolds number ( Re ) is chosen to be e 100 R = and the
spacing ratio L / D is set at 0.5, 1.5, 2.5, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0
and 10.0. Results show that, as in the case of four cylinders in an inline
rectangular configuration , flow fields show four different
features depending on the spacing (single square cylinder, stable
shielding flow, wiggling shielding flow and a vortex shedding flow)
are observed in this study. The effects of spacing ratio on physical
quantities such as mean drag coefficient, Strouhal number and rootmean-
square value of the drag and lift coefficients are also presented.
There is more than one shedding frequency at small spacing ratios.
The mean drag coefficients for downstream cylinders are less than
that of the single cylinder for all spacing ratios. The present results
using the LBM are compared with some existing experimental data
and numerical studies. The comparison shows that the LBM can
capture the characteristics of the bluff body flow reasonably well and
is a good tool for bluff body flow studies.
Abstract: The construction of a civil structure inside a urban
area inevitably modifies the outdoor microclimate at the building
site. Wind speed, wind direction, air pollution, driving rain, radiation
and daylight are some of the main physical aspects that are subjected
to the major changes. The quantitative amount of these modifications
depends on the shape, size and orientation of the building and on its
interaction with the surrounding environment.The flow field over a
flat roof model building has been numerically investigated in order to
determine two-dimensional CFD guidelines for the calculation of the
turbulent flow over a structure immersed in an atmospheric boundary
layer. To this purpose, a complete validation campaign has been
performed through a systematic comparison of numerical simulations
with wind tunnel experimental data.Several turbulence models and
spatial node distributions have been tested for five different vertical
positions, respectively from the upstream leading edge to the
downstream bottom edge of the analyzed model. Flow field
characteristics in the neighborhood of the building model have been
numerically investigated, allowing a quantification of the capabilities
of the CFD code to predict the flow separation and the extension of
the recirculation regions.The proposed calculations have allowed the
development of a preliminary procedure to be used as a guidance in
selecting the appropriate grid configuration and corresponding
turbulence model for the prediction of the flow field over a twodimensional
roof architecture dominated by flow separation.
Abstract: This paper proposed high level feature for online Lao handwritten recognition. This feature must be high level enough so that the feature is not change when characters are written by different persons at different speed and different proportion (shorter or longer stroke, head, tail, loop, curve). In this high level feature, a character is divided in to sequence of curve segments where a segment start where curve reverse rotation (counter clockwise and clockwise). In each segment, following features are gathered cumulative change in direction of curve (- for clockwise), cumulative curve length, cumulative length of left to right, right to left, top to bottom and bottom to top ( cumulative change in X and Y axis of segment). This feature is simple yet robust for high accuracy recognition. The feature can be gather from parsing the original time sampling sequence X, Y point of the pen location without re-sampling. We also experiment on other segmentation point such as the maximum curvature point which was widely used by other researcher. Experiments results show that the recognition rates are at 94.62% in comparing to using maximum curvature point 75.07%. This is due to a lot of variations of turning points in handwritten.
Abstract: The intrusion detection problem has been frequently studied, but intrusion detection methods are often based on a single point of view, which always limits the results. In this paper, we introduce a new intrusion detection model based on the combination of different current methods. First we use a notion of distance to unify the different methods. Second we combine these methods using the Pearson correlation coefficients, which measure the relationship between two methods, and we obtain a combined distance. If the combined distance is greater than a predetermined threshold, an intrusion is detected. We have implemented and tested the combination model with two different public data sets: the data set of masquerade detection collected by Schonlau & al., and the data set of program behaviors from the University of New Mexico. The results of the experiments prove that the combination model has better performances.
Abstract: Titanium alloys like Ti-6Al-2Sn-4Zr-6Mo (Ti-
6246) are widely used in aerospace applications. Component
manufacturing, however, is difficult and expensive as their
machinability is extremely poor. A thorough understanding of the
chip formation process is needed to improve related metal cutting
operations.In the current study, orthogonal cutting experiments have
been performed and theresulting chips were analyzed by optical
microscopy and scanning electron microscopy.Chips from aTi-
6246ingot were produced at different cutting speeds and cutting
depths. During the experiments, depending of the cutting conditions,
continuous or segmented chips were formed. Narrow, highly
deformed and grain oriented zones, the so-called shear zone,
separated individual segments. Different material properties have
been measured in the shear zones and the segments.
Abstract: This paper reports a new pattern recognition approach for face recognition. The biological model of light receptors - cones and rods in human eyes and the way they are associated with pattern vision in human vision forms the basis of this approach. The functional model is simulated using CWD and WPD. The paper also discusses the experiments performed for face recognition using the features extracted from images in the AT & T face database. Artificial Neural Network and k- Nearest Neighbour classifier algorithms are employed for the recognition purpose. A feature vector is formed for each of the face images in the database and recognition accuracies are computed and compared using the classifiers. Simulation results show that the proposed method outperforms traditional way of feature extraction methods prevailing for pattern recognition in terms of recognition accuracy for face images with pose and illumination variations.
Abstract: Two approaches for model development of a smart acoustic box are suggested in this paper: the finite element (FE) approach and the subspace identification. Both approaches result in a state-space model, which can be used for obtaining the frequency responses and for the controller design. In order to validate the developed FE model and to perform the subspace identification, an experimental set-up with the acoustic box and dSPACE system was used. Experimentally obtained frequency responses show good agreement with the frequency responses obtained from the FE model and from the identified model.
Abstract: Ground-source heat pumps achieve higher efficiencies
than conventional air-source heat pumps because they exchange heat
with the ground that is cooler in summer and hotter in winter than the
air environment. Earth heat exchangers are essential parts of the
ground-source heat pumps and the accurate prediction of their
performance is of fundamental importance. This paper presents the
development and validation of a numerical model through an
incompressible fluid flow, for the simulation of energy and
temperature changes in and around a U-tube borehole heat
exchanger. The FlexPDE software is used to solve the resulting
simultaneous equations that model the heat exchanger. The validated
model (through a comparison with experimental data) is then used to
extract conclusions on how various parameters like the U-tube
diameter, the variation of the ground thermal conductivity and
specific heat and the borehole filling material affect the temperature
of the fluid.
Abstract: This paper made an attempt to investigate the problem associated with enhancement of emulsions of light crude oil-water recovery in an oil field of Algerian Sahara. Measurements were taken through experiments using RheoStress (RS600). Factors such as shear rate, temperature and light oil concentration on the viscosity behavior were considered. Experimental measurements were performed in terms of shear stress–shear rate, yield stress and flow index on mixture of light crude oil–water. The rheological behavior of emulsion showed Non-Newtonian shear thinning behavior (Herschel-Bulkley). The experiments done in the laboratory showed the stability of some water in light crude oil emulsions form during consolidate oil recovery process. To break the emulsion using additives may involve higher cost and could be very expensive. Therefore, further research should be directed to find solution of these problems that have been encountered.
Abstract: Network security attacks are the violation of
information security policy that received much attention to the
computational intelligence society in the last decades. Data mining
has become a very useful technique for detecting network intrusions
by extracting useful knowledge from large number of network data
or logs. Naïve Bayesian classifier is one of the most popular data
mining algorithm for classification, which provides an optimal way
to predict the class of an unknown example. It has been tested that
one set of probability derived from data is not good enough to have
good classification rate. In this paper, we proposed a new learning
algorithm for mining network logs to detect network intrusions
through naïve Bayesian classifier, which first clusters the network
logs into several groups based on similarity of logs, and then
calculates the prior and conditional probabilities for each group of
logs. For classifying a new log, the algorithm checks in which cluster
the log belongs and then use that cluster-s probability set to classify
the new log. We tested the performance of our proposed algorithm by
employing KDD99 benchmark network intrusion detection dataset,
and the experimental results proved that it improves detection rates
as well as reduces false positives for different types of network
intrusions.
Abstract: Classifying biomedical literature is a difficult and
challenging task, especially when a large number of biomedical
articles should be organized into a hierarchical structure. In this paper,
we present an approach for classifying a collection of biomedical text
abstracts downloaded from Medline database with the help of
ontology alignment. To accomplish our goal, we construct two types
of hierarchies, the OHSUMED disease hierarchy and the Medline
abstract disease hierarchies from the OHSUMED dataset and the
Medline abstracts, respectively. Then, we enrich the OHSUMED
disease hierarchy before adapting it to ontology alignment process for
finding probable concepts or categories. Subsequently, we compute
the cosine similarity between the vector in probable concepts (in the
“enriched" OHSUMED disease hierarchy) and the vector in Medline
abstract disease hierarchies. Finally, we assign category to the new
Medline abstracts based on the similarity score. The results obtained
from the experiments show the performance of our proposed approach
for hierarchical classification is slightly better than the performance of
the multi-class flat classification.
Abstract: In an era of knowledge explosion, the growth of data
increases rapidly day by day. Since data storage is a limited resource,
how to reduce the data space in the process becomes a challenge issue.
Data compression provides a good solution which can lower the
required space. Data mining has many useful applications in recent
years because it can help users discover interesting knowledge in large
databases. However, existing compression algorithms are not
appropriate for data mining. In [1, 2], two different approaches were
proposed to compress databases and then perform the data mining
process. However, they all lack the ability to decompress the data to
their original state and improve the data mining performance. In this
research a new approach called Mining Merged Transactions with the
Quantification Table (M2TQT) was proposed to solve these problems.
M2TQT uses the relationship of transactions to merge related
transactions and builds a quantification table to prune the candidate
itemsets which are impossible to become frequent in order to improve
the performance of mining association rules. The experiments show
that M2TQT performs better than existing approaches.
Abstract: In this paper, we propose effective system for digital music retrieval. We divided proposed system into Client and Server. Client part consists of pre-processing and Content-based feature extraction stages. In pre-processing stage, we minimized Time code Gap that is occurred among same music contents. As content-based feature, first-order differentiated MFCC were used. These presented approximately envelop of music feature sequences. Server part included Music Server and Music Matching stage. Extracted features from 1,000 digital music files were stored in Music Server. In Music Matching stage, we found retrieval result through similarity measure by DTW. In experiment, we used 450 queries. These were made by mixing different compression standards and sound qualities from 50 digital music files. Retrieval accurate indicated 97% and retrieval time was average 15ms in every single query. Out experiment proved that proposed system is effective in retrieve digital music and robust at various user environments of web.
Abstract: This paper presents a remote on-line diagnostic system
for vehicles via the use of On-Board Diagnostic (OBD), GPS, and 3G
techniques. The main parts of the proposed system are on-board
computer, vehicle monitor server, and vehicle status browser. First,
the on-board computer can obtain the location of deriver and vehicle
status from GPS receiver and OBD interface, respectively. Then
on-board computer will connect with the vehicle monitor server
through 3G network to transmit the real time vehicle system status.
Finally, vehicle status browser could show the remote vehicle status
including vehicle speed, engine rpm, battery voltage, engine coolant
temperature, and diagnostic trouble codes. According to the
experimental results, the proposed system can help fleet managers and
car knockers to understand the remote vehicle status. Therefore this
system can decrease the time of fleet management and vehicle repair
due to the fleet managers and car knockers who find the diagnostic
trouble messages in time.
Abstract: The objective of the research was to evaluate the
quality of milk pomade sweet – sherbet packed in different packaging
materials (Multibarrier 60, met.BOPET/PE, Aluthen), by several
packaging technologies – active and modified atmosphere (MAP)
(consisting of 100% CO2), and control – in air ambiance.
Experiments were carried out at the Faculty of Food Technology of
Latvia University of Agriculture. Samples were stored at the room
temperature +21±1 °C. The physiochemical properties – weight
losses, moisture, hardening, colour and changes in headspace
atmosphere concentration (CO2 and O2) of packs were analysed
before packaging and after 2, 4, 6, 8, 10 and 12 storage weeks.
Abstract: In order to study the effect of plant density and
competition of wheat with field bindweed (Convolvulus arvensis) on
yield and agronomical properties of wheat(Triticum Sativum) in
irrigated conditions, a factorial experiment as the base of complete
randomize block design in three replication was conducted at the
field of Kamalvand in khoramabad (Lorestan) region of Iran during
2008-2009. Three plant density (Factor A=200, 230 and 260kg/ha)
three cultivar (Factor B=Bahar,Pishtaz and Alvand) and weed control
(Factor C= control and no control of weeds)were assigned in
experiment. Results show that: Plant density had significant effect
(statistically) on seed yield, 1000 seed weight, weed density and dry
weight of weeds, seed yield and harvest index had been meaningful
effect for cultivars. The interaction between plant density and
cultivars for weed density, seed yield, thousand seed weight and
harvest index were significant. 260 kg/ha (plant density) of wheat had
more effect on increasing of seed yield in Bahar cultivar wheat in
khoramabad region of Iran.
Abstract: Abrasive waterjet is a novel machining process capable of processing wide range of hard-to-machine materials. This research addresses modeling and optimization of the process parameters for this machining technique. To model the process a set of experimental data has been used to evaluate the effects of various parameter settings in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. Depth of cut, as one of the most important output characteristics, has been evaluated based on different parameter settings. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. The pairwise effects of process parameters settings on process response outputs are also shown graphically. The proposed model is then embedded into a Simulated Annealing algorithm to optimize the process parameters. The optimization is carried out for any desired values of depth of cut. The objective is to determine proper levels of process parameters in order to obtain a certain level of depth of cut. Computational results demonstrate that the proposed solution procedure is quite effective in solving such multi-variable problems.
Abstract: In this work we investigated the behavior of methane
hydrates dispersed in crude oils from different fields at temperatures
below 0°C. In case of crude oil emulsion the size of water droplets is
in the range of 50e100"m. The size of hydrate particles formed from
droplets is the same. The self-preservation is not expected in this
field. However, the self-preservation of hydrates with the size of
particles 24±18"m (electron microscopy data) in suspensions is
observed. Similar results were obtained for four different kinds of
crude oil and model system such as asphaltenes, resins and wax in ndecane.
This result can allow developing effective methods to prevent
the formation and elimination of gas-hydrate plugs in pipelines under
low temperature conditions (e. g. in Eastern Siberia). There is a
prospective to use experiment results for working out the technology
of associated petroleum gas recovery.
Abstract: This paper presents a sensing system for 3D sensing
and mapping by a tracked mobile robot with an arm-type sensor
movable unit and a laser range finder (LRF). The arm-type sensor
movable unit is mounted on the robot and the LRF is installed at the
end of the unit. This system enables the sensor to change position and
orientation so that it avoids occlusions according to terrain by this
mechanism. This sensing system is also able to change the height of
the LRF by keeping its orientation flat for efficient sensing. In this kind
of mapping, it may be difficult for moving robot to apply mapping
algorithms such as the iterative closest point (ICP) because sets of the
2D data at each sensor height may be distant in a common surface. In
order for this kind of mapping, the authors therefore applied
interpolation to generate plausible model data for ICP. The results of
several experiments provided validity of these kinds of sensing and
mapping in this sensing system.