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: The cables in a nuclear power plant are designed to be
used for about 40 years in safe operation environment. However, the
heat and radiation in the nuclear power plant causes the rapid
performance deterioration of cables in nuclear vessels and heat
exchangers, which requires cable lifetime estimation. The most
accurate method of estimating the cable lifetime is to evaluate the
cables in a laboratory. However, removing cables while the plant is
operating is not allowed because of its safety and cost. In this paper, a
robot system to estimate the cable lifetime in nuclear power plants is
developed and tested. The developed robot system can calculate a
modulus value to estimate the cable lifetime even when the nuclear
power plant is in operation.
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: In this article, various models of surface tension force (CSF, CSS and PCIL) for interfacial flows have been applied to dynamic case and the results were compared. We studied the Kelvin- Helmholtz instabilities, which are produced by shear at the interface between two fluids with different physical properties. The velocity inlet is defined as a sinusoidal perturbation. When gravity and surface tension are taking into account, we observe the development of the Instability for a critic value of the difference of velocity of the both fluids. The VOF Model enables to simulate Kelvin-Helmholtz Instability as dynamic case.
Abstract: Study of fire and explosion is very important mainly
in oil and gas industries due to several accidents which have been
reported in the past and present. In this work, we have investigated
the flammability of bio oil vapour mixtures. This mixture may
contribute to fire during the storage and transportation process. Bio
oil sample derived from Palm Kernell shell was analysed using Gas
Chromatography Mass Spectrometry (GC-MS) to examine the
composition of the sample. Mole fractions of 12 selected
components in the liquid phase were obtained from the GC-FID data
and used to calculate mole fractions of components in the gas phase
via modified Raoult-s law. Lower Flammability Limits (LFLs) and
Upper Flammability Limits (UFLs) for individual components were
obtained from published literature. However, stoichiometric
concentration method was used to calculate the flammability limits
of some components which their flammability limit values are not
available in the literature. The LFL and UFL values for the mixture
were calculated using the Le Chatelier equation. The LFLmix and
UFLmix values were used to construct a flammability diagram and
subsequently used to determine the flammability of the mixture. The
findings of this study can be used to propose suitable inherently
safer method to prevent the flammable mixture from occurring and
to minimizing the loss of properties, business, and life due to fire
accidents in bio oil productions.
Abstract: Semisolid metal processing uses solid–liquid slurries
containing fine and globular solid particles uniformly distributed in a
liquid matrix, which can be handled as a solid and flow like a liquid.
In the recent years, many methods have been introduced for the
production of semisolid slurries since it is scientifically sound and
industrially viable with such preferred microstructures called
thixotropic microstructures as feedstock materials. One such process
that needs very low equipment investment and running costs is the
cooling slope. In this research by using a mechanical stirrer slurry
maker constructed by the authors, the effects of mechanical stirring
parameters such as: stirring time, stirring temperature and stirring
Speed on micro-structure and mechanical properties of A360
aluminum alloy in semi-solid forming, are investigated. It is
determined that mold temperature and holding time of part in
temperature of 580ºC have a great effect on micro-structure and
mechanical properties(stirring temperature of 585ºC, stirring time of
20 minutes and stirring speed of 425 RPM). By optimizing the
forming parameters, dendrite microstructure changes to globular and
mechanical properties improves. This is because of breaking and
globularzing dendrites of primary α-AL.
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: Numerical study of two dimensional supersonic
hydrogen-air mixing layer is performed to investigate the effect of
turbulence and chemical additive on ignition distance. Chemical
reaction is treated using detail kinetics. Advection upstream splitting
method is used to calculate the fluxes and one equation turbulence
model is chosen here to simulate the considered problem. Hydrogen
peroxide is used as an additive and the results show that inflow
turbulence and chemical additive may drastically decrease the
ignition delay in supersonic combustion.
Abstract: Currently, there are many local area industrial networks
that can give guaranteed bandwidth to synchronous traffic, particularly
providing CBR channels (Constant Bit Rate), which allow
improved bandwidth management. Some of such networks operate
over Ethernet, delivering channels with enough capacity, specially
with compressors, to integrate multimedia traffic in industrial monitoring
and image processing applications with many sources. In
these industrial environments where a low latency is an essential
requirement, JPEG is an adequate compressing technique but it
generates VBR traffic (Variable Bit Rate). Transmitting VBR traffic
in CBR channels is inefficient and current solutions to this problem
significantly increase the latency or further degrade the quality. In
this paper an R(q) model is used which allows on-line calculation of
the JPEG quantification factor. We obtained increased quality, a lower
requirement for the CBR channel with reduced number of discarded
frames along with better use of the channel bandwidth.
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: We introduce, a new interactive 3D simulation system of ocular motion and expressions suitable for: (1) character animation applications to game design, film production, HCI (Human Computer Interface), conversational animated agents, and virtual reality; (2) medical applications (ophthalmic neurological and muscular pathologies: research and education); and (3) real time simulation of unconscious cognitive and emotional responses (for use, e.g., in psychological research). The system is comprised of: (1) a physiologically accurate parameterized 3D model of the eyes, eyelids, and eyebrow regions; and (2) a prototype device for realtime control of eye motions and expressions, including unconsciously produced expressions, for application as in (1), (2), and (3) above. The 3D eye simulation system, created using state-of-the-art computer animation technology and 'optimized' for use with an interactive and web deliverable platform, is, to our knowledge, the most advanced/realistic available so far for applications to character animation and medical pedagogy.
Abstract: In this paper we present a system for classifying videos
by frequency spectra. Many videos contain activities with repeating
movements. Sports videos, home improvement videos, or videos
showing mechanical motion are some example areas. Motion of these
areas usually repeats with a certain main frequency and several side
frequencies. Transforming repeating motion to its frequency domain
via FFT reveals these frequencies. Average amplitudes of frequency
intervals can be seen as features of cyclic motion. Hence determining
these features can help to classify videos with repeating movements.
In this paper we explain how to compute frequency spectra for video
clips and how to use them for classifying. Our approach utilizes series
of image moments as a function. This function again is transformed
into its frequency domain.
Abstract: One major difficulty that faces developers of
concurrent and distributed software is analysis for concurrency based
faults like deadlocks. Petri nets are used extensively in the
verification of correctness of concurrent programs. ECATNets [2] are
a category of algebraic Petri nets based on a sound combination of
algebraic abstract types and high-level Petri nets. ECATNets have
'sound' and 'complete' semantics because of their integration in
rewriting logic [12] and its programming language Maude [13].
Rewriting logic is considered as one of very powerful logics in terms
of description, verification and programming of concurrent systems.
We proposed in [4] a method for translating Ada-95 tasking
programs to ECATNets formalism (Ada-ECATNet). In this paper,
we show that ECATNets formalism provides a more compact
translation for Ada programs compared to the other approaches based
on simple Petri nets or Colored Petri nets (CPNs). Such translation
doesn-t reduce only the size of program, but reduces also the number
of program states. We show also, how this compact Ada-ECATNet
may be reduced again by applying reduction rules on it. This double
reduction of Ada-ECATNet permits a considerable minimization of
the memory space and run time of corresponding Maude program.
Abstract: As application of re-activation of backside on power
device Insulated Gate Bipolar Transistor (IGBT), laser annealing was
employed to irradiate amorphous silicon substrate, and resistivities
were measured using four point probe measurement. For annealing
the amorphous silicon two lasers were used at wavelength of visible
green (532 nm) together with Infrared (793 nm). While the green
laser efficiently increased temperature at top surface the Infrared
laser reached more deep inside and was effective for melting the
top surface. A finite element method was employed to evaluate time
dependent thermal distribution in silicon substrate.
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: In this report, an OTA which is used in fully
differential pipelined ADC was described. Using gain-boost
architecture with difference-ended amplifier, this OTA achieve
high-gain and high-speed. Besides, the CMFB circuit is also used, and
some methods are concerned to improve the performance. Then, by
optimization the layout design, OTA-s mismatch was reduced. This
design was using TSMC 0.18um CMOS process and simulation both
schematic and layout in Cadence. The result of the simulation shows
that the OTA has a gain up to 80dB,a unity gain bandwidth of about
1.437GHz for a 2pF load, a slew rate is about 428V/μs, a output swing
is 0.2V~1.35V, with the power supply of 1.8V, the power
consumption is 88mW. This amplifier was used in a 10bit 150MHz
pipelined ADC.
Abstract: Monitoring the tool flank wear without affecting the
throughput is considered as the prudent method in production
technology. The examination has to be done without affecting the
machining process. In this paper we proposed a novel work that is
used to determine tool flank wear by observing the sound signals
emitted during the turning process. The work-piece material we used
here is steel and aluminum and the cutting insert was carbide
material. Two different cutting speeds were used in this work. The
feed rate and the cutting depth were constant whereas the flank wear
was a variable. The emitted sound signal of a fresh tool (0 mm flank
wear) a slightly worn tool (0.2 -0.25 mm flank wear) and a severely
worn tool (0.4mm and above flank wear) during turning process were
recorded separately using a high sensitive microphone. Analysis
using Singular Value Decomposition was done on these sound
signals to extract the feature sound components. Observation of the
results showed that an increase in tool flank wear correlates with an
increase in the values of SVD features produced out of the sound
signals for both the materials. Hence it can be concluded that wear
monitoring of tool flank during turning process using SVD features
with the Fuzzy C means classification on the emitted sound signal is
a potential and relatively simple method.
Abstract: Prediction of fault-prone modules provides one way to
support software quality engineering. Clustering is used to determine
the intrinsic grouping in a set of unlabeled data. Among various
clustering techniques available in literature K-Means clustering
approach is most widely being used. This paper introduces K-Means
based Clustering approach for software finding the fault proneness of
the Object-Oriented systems. The contribution of this paper is that it
has used Metric values of JEdit open source software for generation
of the rules for the categorization of software modules in the
categories of Faulty and non faulty modules and thereafter
empirically validation is performed. The results are measured in
terms of accuracy of prediction, probability of Detection and
Probability of False Alarms.
Abstract: A numerical investigation of surface heat transfer
characteristics of turbulent air flows in different parallel plate
grooved channels is performed using CFD code. The results are
obtained for Reynolds number ranging from 10,000 to 30,000 and for
arc-shaped and rectangular grooved channels. The influence of
different geometric parameters of dimples as well as the number of
them and the geometric and thermophysical properties of channel
walls are studied. It is found that there exists an optimum value for
depth of dimples in which the largest wall heat flux can be achieved.
Also, the results show a critical value for the ratio of wall thermal
conductivity to the one of fluid in which the dependence of wall heat
flux to this ratio almost vanishes. In most cases examined, heat
transfer enhancement is larger for arc-shaped grooved channels than
rectangular ones.