Abstract: This paper gives an overview of a deep drawing
process by pressurized liquid medium separated from the sheet by a
rubber diaphragm. Hydroforming deep drawing processing of sheet
metal parts provides a number of advantages over conventional
techniques. It generally increases the depth to diameter ratio possible
in cup drawing and minimizes the thickness variation of the drawn
cup. To explore the deformation mechanism, analytical and
numerical simulations are used for analyzing the drawing process of
an AA6061-T4 blank. The effects of key process parameters such as
coefficient of friction, initial thickness of the blank and radius
between cup wall and flange are investigated analytically and
numerically. The simulated results were in good agreement with the
results of the analytical model. According to finite element
simulations, the hydroforming deep drawing method provides a more
uniform thickness distribution compared to conventional deep
drawing and decreases the risk of tearing during the process.
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: In this paper, we apply a semismooth active set method to image inpainting. The method exploits primal and dual features of a proposed regularized total variation model, following after the technique presented in [4]. Numerical results show that the method is fast and efficient in inpainting sufficiently thin domains.
Abstract: Trends in business intelligence, e-commerce and
remote access make it necessary and practical to store data in
different ways on multiple systems with different operating systems.
As business evolve and grow, they require efficient computerized
solution to perform data update and to access data from diverse
enterprise business applications. The objective of this paper is to
demonstrate the capability of DTS [1] as a database solution for
automatic data transfer and update in solving business problem. This
DTS package is developed for the sales of variety of plants and
eventually expanded into commercial supply and landscaping
business. Dimension data modeling is used in DTS package to
extract, transform and load data from heterogeneous database
systems such as MySQL, Microsoft Access and Oracle that
consolidates into a Data Mart residing in SQL Server. Hence, the
data transfer from various databases is scheduled to run automatically
every quarter of the year to review the efficient sales analysis.
Therefore, DTS is absolutely an attractive solution for automatic data
transfer and update which meeting today-s business needs.
Abstract: Potatoes are a good source of carotenoids, which are lipophilic compounds synthesized in plastids from isoprenoids. The aim of this research was to determine the content of carotenoids in relationship with the colour of organically and conventionally cultivated potato genotypes before and after period of storage. In cooperation with the State Priekuli Plant Breeding Institute (Latvia), six potato genotypes were studied: 'Agrie dzeltenie', 'Prelma', 'Imanta', 'S-03135-10', 'S-99108-8' and 'S-01063-5'. All the genotypes were cultivated under three different conditions: organically and conventionally (two conditions). The content of carotenoids was determined by using spectrophotometer and the colour – L*a*b* system. The results of current research show that after the period of storage, carotenoid amount has increased and in conventionally cultivated potatoes it varies from 228.514 to 552.434 μg 100 g-1 while in organically cultivated potato genotypes – from 45.485 to 662.699 μg 100 g-1 FW. Colour of potato flesh was changing during storage.
Abstract: Fuzzy C-means Clustering algorithm (FCM) is a
method that is frequently used in pattern recognition. It has the
advantage of giving good modeling results in many cases, although,
it is not capable of specifying the number of clusters by itself. In
FCM algorithm most researchers fix weighting exponent (m) to a
conventional value of 2 which might not be the appropriate for all
applications. Consequently, the main objective of this paper is to use
the subtractive clustering algorithm to provide the optimal number of
clusters needed by FCM algorithm by optimizing the parameters of
the subtractive clustering algorithm by an iterative search approach
and then to find an optimal weighting exponent (m) for the FCM
algorithm. In order to get an optimal number of clusters, the iterative
search approach is used to find the optimal single-output Sugenotype
Fuzzy Inference System (FIS) model by optimizing the
parameters of the subtractive clustering algorithm that give minimum
least square error between the actual data and the Sugeno fuzzy
model. Once the number of clusters is optimized, then two
approaches are proposed to optimize the weighting exponent (m) in
the FCM algorithm, namely, the iterative search approach and the
genetic algorithms. The above mentioned approach is tested on the
generated data from the original function and optimal fuzzy models
are obtained with minimum error between the real data and the
obtained fuzzy models.
Abstract: Flow through micro and mini channels requires relatively
high driving pressure due to the large fluid pressure drop
through these channels. Consequently the forces acting on the walls of
the channel due to the fluid pressure are also large. Due to these forces
there are displacement fields set up in the solid substrate containing
the channels. If the movement of the substrate is constrained at some
points, then stress fields are established in the substrate. On the other
hand, if the deformation of the channel shape is sufficiently large
then its effect on the fluid flow is important to be calculated. Such
coupled fluid-solid systems form a class of problems known as fluidstructure
interactions. In the present work a co-located finite volume
discretization procedure on unstructured meshes is described for
solving fluid-structure interaction type of problems. A linear elastic
solid is assumed for which the effect of the channel deformation
on the flow is neglected. Thus the governing equations for the
fluid and the solid are decoupled and are solved separately. The
procedure is validated by solving two benchmark problems, one from
fluid mechanics and another from solid mechanics. A fluid-structure
interaction problem of flow through a U-shaped channel embedded
in a plate is solved.
Abstract: The advances in location-based data collection
technologies such as GPS, RFID etc. and the rapid reduction of their
costs provide us with a huge and continuously increasing amount of
data about movement of vehicles, people and goods in an urban area.
This explosive growth of geospatially-referenced data has far
outpaced the planner-s ability to utilize and transform the data into
insightful information thus creating an adverse impact on the return
on the investment made to collect and manage this data. Addressing
this pressing need, we designed and developed DIVAD, a dynamic
and interactive visual analytics dashboard to allow city planners to
explore and analyze city-s transportation data to gain valuable
insights about city-s traffic flow and transportation requirements. We
demonstrate the potential of DIVAD through the use of interactive
choropleth and hexagon binning maps to explore and analyze large
taxi-transportation data of Singapore for different geographic and
time zones.
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: In this paper, the effects of the restoring force device on the response of a space frame structure resting on sliding type of bearing with a restoring force device is studied. The NS component of the El - Centro earthquake and harmonic ground acceleration is considered for earthquake excitation. The structure is modeled by considering six-degrees of freedom (three translations and three rotations) at each node. The sliding support is modeled as a fictitious spring with two horizontal degrees of freedom. The response quantities considered for the study are the top floor acceleration, base shear, bending moment and base displacement. It is concluded from the study that the displacement of the structure reduces by the use of the restoring force device. Also, the peak values of acceleration, bending moment and base shear also decreases. The simulation results show the effectiveness of the developed and proposed method.
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: Wireless sensor networks have been used in wide
areas of application and become an attractive area for researchers in
recent years. Because of the limited energy storage capability of
sensor nodes, Energy consumption is one of the most challenging
aspects of these networks and different strategies and protocols deals
with this area. This paper presents general methods for designing low
power wireless sensor network. Different sources of energy
consumptions in these networks are discussed here and techniques for
alleviating the consumption of energy are presented.
Abstract: Phytases are acid phosphatase enzymes, which
efficiently cleave phosphate moieties from phytic acid, thereby
generating myo-inositol and inorganic phosphate. Thirty four
isolates of endophytic fungi to produce of phytases were isolated
from leaf, stem and root fragments of soybean. Screening of 34
isolates of endophytic fungi identified the phytases produced by
Rhizoctonia sp. and Fusarium verticillioides . The phytase
production were the best induced by phytic acid and rice bran
compared the others inducer in submerged fermentation medium
used. The phytase produced by both Rhizoctonia sp. and F.
verticillioides have pH optimum at 4.0 and 5.0 respectively. The
characterization of phytase from Fusarium verticillioides showed that
temperature optimum was 500C and stability until 600C, the pH
optimum 5.0 and pH stability was 2.5 – 6.0, and substrate specificity
were rice bran>soybean meal>corn> coconut cake, respectively.
Abstract: Artificial Immune System is applied as a Heuristic
Algorithm for decades. Nevertheless, many of these applications
took advantage of the benefit of this algorithm but seldom proposed
approaches for enhancing the efficiency. In this paper, a
Self-evolving Artificial Immune System is proposed via developing
the T and B cell in Immune System and built a self-evolving
mechanism for the complexities of different problems. In this
research, it focuses on enhancing the efficiency of Clonal selection
which is responsible for producing Affinities to resist the invading of
Antigens. T and B cell are the main mechanisms for Clonal
Selection to produce different combinations of Antibodies.
Therefore, the development of T and B cell will influence the
efficiency of Clonal Selection for searching better solution.
Furthermore, for better cooperation of the two cells, a co-evolutional
strategy is applied to coordinate for more effective productions of
Antibodies. This work finally adopts Flow-shop scheduling
instances in OR-library to validate the proposed algorithm.
Abstract: In the age of global communications, heterogeneous
networks are seen to be the best choice of strategy to ensure continuous and uninterruptible services. This will allow mobile
terminal to stay in connection even they are migrating into different segment coverage through the handoff process. With the increase of
teletraffic demands in mobile cellular system, hierarchical cellular systems have been adopted extensively for more efficient channel
utilization and better QoS (Quality of Service). This paper presents a
bidirectional call overflow scheme between two layers of microcells and macrocells, where handoffs are decided by the velocity of mobile
making the call. To ensure that handoff calls are given higher priorities, it is assumed that guard channels are assigned in both
macrocells and microcells. A hysteresis value introduced in mobile velocity is used to allow mobile roam in the same cell if its velocity
changes back within the set threshold values. By doing this the number of handoffs is reduced thereby reducing the processing overhead and enhancing the quality of service to the end user.
Abstract: A predictive clustering hybrid regression (pCHR)
approach was developed and evaluated using dataset from H2-
producing sucrose-based bioreactor operated for 15 months. The aim
was to model and predict the H2-production rate using information
available about envirome and metabolome of the bioprocess. Selforganizing
maps (SOM) and Sammon map were used to visualize the
dataset and to identify main metabolic patterns and clusters in
bioprocess data. Three metabolic clusters: acetate coupled with other
metabolites, butyrate only, and transition phases were detected. The
developed pCHR model combines principles of k-means clustering,
kNN classification and regression techniques. The model performed
well in modeling and predicting the H2-production rate with mean
square error values of 0.0014 and 0.0032, respectively.
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: 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.