Abstract: The present study explains the somatic marker theory of Antonio Damasio, which indicates that when making a decision, the stored or possible future scenarios (future memory) images allow people to feel for a moment what would happen when they make a choice, and how this is emotionally marked. This process can be conscious or unconscious. The development of new Neuromarketing techniques such as functional magnetic resonance imaging (fMRI), carries a greater understanding of how the brain functions and consumer behavior. In the results observed in different studies using fMRI, the evidence suggests that the somatic marker and future memories influence the decision-making process, adding a positive or negative emotional component to the options. This would mean that all decisions would involve a present emotional component, with a rational cost-benefit analysis that can be performed later.
Abstract: In this study, total fatty acid composition of muscle
lipids of Cyprinus carpio L. living in Suğla Dam Lake, Altinapa Dam
Lake, Eğirdir Lake and Burdur Lake were determined using GC.
During this study, for the summer season of July was taken from each
region of the land and they were stored in deep-freeze set to -20
degrees until the analysis date. At the end of the analyses, 30
different fatty acids were found in the composition of Cyprinus
carpio L. which lives in different lakes. Cyprinus carpio Suğla Dam
Lake of polyunsaturated fatty acids (PUFAs), were higher than other
lakes. Cyprinus carpio L. was the highest in the major SFA palmitic
acid. Polyunsaturated fatty acids (PUFA) of carp, the most abundant
fish species in all lakes, were found to be higher than those of
saturated fatty acids (SFA) in all lakes. Palmitic acid was the major
SFA in all lakes. Oleic acid was identified as the major MUFA.
Docosahexaenoic acid (DHA) was the most abundant in all lakes. ω3
fatty acid composition was higher than the percentage of the
percentage ω6 fatty acids in all lake. ω3/ω6 rates of Cyprinus carpio
L. Suğla Dam Lake, Altinapa Dam Lake, Eğirdir Lake and Burdur
Lake, 2.12, 1.19, 2.15, 2.87, and 2.82, respectively. Docosahexaenoic
acid (DHA) was the major PUFA in Eğirdir and Burdur lakes,
whereas linoleic acid (LA) was the major PUFA in Altinapa and
Suğla Dam Lakes. It was shown that the fatty acid composition in the
muscle of carp was significantly influenced by different lakes.
Abstract: The aim of the study was to investigate the effect of
Saccharomyces cerevisiae (SC) live yeast culture on microbial
protein supply to small intestine in Kivircik male yearlings when fed
with different ratio of forage and concentrate diets. Four Kivircik
male yearlings with permanent rumen canula were used in the
experiment. The treatments were allocated to a 4x4 Latin square
design. Diet I consisted of 70% alfalfa hay and 30% concentrate, Diet
II consisted of 30% alfalfa hay and 70% concentrate, Diet I and II
were supplemented with a SC. Daily urine was collected and stored at
-20°C until analysis. Calorimetric methods were used for the
determination of urinary allantoin and creatinine levels. The
estimated microbial N supply to small intestine for Diets I, I+SC, II
and II+SC were 2.51, 2.64, 2.95 and 3.43 g N/d respectively.
Supplementation of Diets I and II with SC significantly affected the
allantoin levels in μmol/W0.75 (p
Abstract: The Petri nets are the first standard for business
process modeling. Most probably, it is one of the core reasons why
all new standards created afterwards have to be so reformed as to
reach the stage of mapping the new standard onto Petri nets. The paper presents a business process repository based on a
universal database. The repository provides the possibility the data
about a given process to be stored in three different ways. Business
process repository is developed with regard to the reformation of a
given model to a Petri net in order to be easily simulated. Two different techniques for business process simulation based on
Petri nets - Yasper and Woflan are discussed. Their advantages and
drawbacks are outlined. The way of simulating business process
models, stored in the Business process repository is shown.
Abstract: For the last decade, researchers have started to focus
their interest on Multicast Group Key Management Framework. The
central research challenge is secure and efficient group key
distribution. The present paper is based on the Bit model based
Secure Multicast Group key distribution scheme using the most
popular absolute encoder output type code named Gray Code. The
focus is of two folds. The first fold deals with the reduction of
computation complexity which is achieved in our scheme by
performing fewer multiplication operations during the key updating
process. To optimize the number of multiplication operations, an
O(1) time algorithm to multiply two N-bit binary numbers which
could be used in an N x N bit-model of reconfigurable mesh is used
in this proposed work. The second fold aims at reducing the amount
of information stored in the Group Center and group members while
performing the update operation in the key content. Comparative
analysis to illustrate the performance of various key distribution
schemes is shown in this paper and it has been observed that this
proposed algorithm reduces the computation and storage complexity
significantly. Our proposed algorithm is suitable for high
performance computing environment.
Abstract: This paper focuses on the orbit avoidance strategy of
the optical remote sensing satellite. The optical remote sensing
satellite, moving along the Sun-synchronous orbit, is equipped with
laser warning equipment to alert CCD camera from laser attacks. This
paper explores the strategy of satellite avoidance to protect the CCD
camera and also the satellite. The satellite could evasive to several
target points in the orbital coordinates of virtual satellite. The so-called
virtual satellite is a passive vehicle which superposes the satellite at the
initial stage of avoidance. The target points share the consistent cycle
time and the same semi-major axis with the virtual satellite, which
ensures the properties of the satellite’s Sun-synchronous orbit remain
unchanged. Moreover, to further strengthen the avoidance capability
of satellite, it can perform multi-target-points avoid maneuvers. On
occasions of fulfilling the satellite orbit tasks, the orbit can be restored
back to virtual satellite through orbit maneuvers. There into, the avoid
maneuvers adopts pulse guidance. In addition, the fuel consumption is
optimized. The avoidance strategy discussed in this article is
applicable to optical remote sensing satellite when it is encountered
with hostile attack of space-based laser anti-satellite.
Abstract: In this paper, a novel fuzzy approach is developed
while solving the Dynamic Routing and Wavelength Assignment
(DRWA) problem in optical networks with Wavelength Division
Multiplexing (WDM). In this work, the effect of nonlinear and linear
impairments such as Four Wave Mixing (FWM) and amplifier
spontaneous emission (ASE) noise are incorporated respectively. The
novel algorithm incorporates fuzzy logic controller (FLC) to reduce
the effect of FWM noise and ASE noise on a requested lightpath
referred in this work as FWM aware fuzzy dynamic routing and
wavelength assignment algorithm. The FWM crosstalk products and
the static FWM noise power per link are pre computed in order to
reduce the set up time of a requested lightpath, and stored in an
offline database. These are retrieved during the setting up of a
lightpath and evaluated online taking the dynamic parameters like
cost of the links into consideration.
Abstract: The study conducted a simulation of the effect of sea
water to the bonding capacity of GFRP sheet on the concrete beams
using a simulation tank. Fiber reinforced polymer (FRP) has been
developed and applied in many fields civil engineering structures on
the new structures and also for strengthening of the deteriorated
structures. The FRP has advantages such as its corrosion resistance as
well as high tensile strength to weight ratio. Compared to the other
FRP materials, Glass composed FRP (GFRP) is relatively cheaper.
GFRP sheet is applied externally by bonding it on the concrete surface.
The studies regarding the application of GFRP sheet have been
conducted such as strengthening system, bonding behavior of GFRP
sheet including the application as reinforcement in new structures. For
application to the structures with direct contact to sea environment, a
study regarding the effect of sea water to the bonding capacity of
GFRP sheet is important to be clarified. To achieve the objective of the
study, a series of concrete beams strengthened with GFRP sheet on
extreme tension surface were prepared. The beams then were stored on
the sea water tank for six months. Results indicated the bonding
capacity decreased after six month exposed to the sea water.
Abstract: On account of the concern of the fossil fuel is
depleting and its negative effects on the environment, interest in
alternative energy sources is increasing day by day. However,
considering the importance of transportation in human life, instead of
oil and its derivatives fueled vehicles with internal combustion
engines, electric vehicles which are sensitive to the environment and
working with electrical energy has begun to develop. In this study,
simulation was carried out for providing energy management and
recovering regenerative braking in fuel cell-battery hybrid electric
vehicle. The main power supply of the vehicle is fuel cell on the other
hand not only instantaneous power is supplied by the battery but also
the energy generated due to regenerative breaking is stored in the
battery. Obtained results of the simulation is analyzed and discussed.
Abstract: One of the major problems being faced by human society is that the global temperature is believed to be rising due to human activity that releases carbon IV Oxide (CO2) to the atmosphere. Carbon IV Oxide is the most important greenhouse gas influencing global warming and possible climate change. With climate change becoming alarming, reducing CO2 in our atmosphere has become a primary goal of international efforts. Forest lands are major sink and could absorb large quantities of carbon if the trees are judiciously managed. The study aims at estimating the carbon sequestration capacity of Pinus caribaea (pine) and Tectona grandis (Teak) under the prevailing environmental conditions and exploring tree growth variables that influences the carbon sequestration capacity in Omo Forest Reserve, Ogun State, Nigeria. Improving forest management by manipulating growth characteristics that influences carbon sequestration could be an adaptive strategy of forestry to climate change. Random sampling was used to select Temporary Sample Plots (TSPs) in the study area from where complete enumeration of growth variables was carried out within the plots. The data collected were subjected to descriptive and correlational analyses. The results showed that average carbon stored by Pine and Teak are 994.4±188.3 Kg and 1350.7±180.6 Kg respectively. The difference in carbon stored in the species is significant enough to consider choice of species relevant in climate change adaptation strategy. Tree growth variables influence the capacity of the tree to sequester carbon. Height, diameter, volume, wood density and age are positively correlated to carbon sequestration. These tree growth variables could be manipulated by the forest manager as an adaptive strategy for climate change while plantations of high wood density species could be relevant for management strategy to increase carbon storage.
Abstract: The enormous amount of information stored on the
web increases from one day to the next, exposing the web currently
faced with the inevitable difficulties of research pertinent information
that users really want. The problem today is not limited to expanding
the size of the information highways, but to design a system for
intelligent search. The vast majority of this information is stored in
relational databases, which in turn represent a backend for managing
RDF data of the semantic web. This problem has motivated us to
write this paper in order to establish an effective approach to support
semantic transformation algorithm for SPARQL queries to SQL
queries, more precisely SPARQL SELECT queries; by adopting this
method, the relational database can be questioned easily with
SPARQL queries maintaining the same performance.
Abstract: Breast cancer is in the top rate of cancer. We analyzed
the prevalence of obesity and its association with breast cancer and
finally we reviewed 25 article that 320 patient and 320 control which
enrolled to our study. The distribution of breast cancer patients and
controls with respect to their anthropometric indices in patients with
higher weight, which was statistically significant (60.2 ± 10.2 kg)
compared with control group (56.1 ± 11.3 kg). The body mass index
of patients was (26.06+/-3.42) and significantly higher than the
control group (24.1+/-1.7). Obesity leads to increased levels of
adipose tissue in the body that can be stored toxins and carcinogens
to produce a continuous supply. Due to the high level of fat and the
role of estrogen in a woman which is endogenous estrogen of the
tumor and regulates the activities of growth steroids, obesity has
confirmed as a risk factor for breast cancer. Our study and other
studies have shown that obesity is a risk factor for breast cancer. And
it can be prevented with a weight loss intervention for breast cancer
in the future.
Abstract: Nowadays, cloud environments are becoming a need for companies, this new technology gives the opportunities to access to the data anywhere and anytime. It also provides an optimized and secured access to the resources and gives more security for the data which is stored in the platform. However, some companies do not trust Cloud providers, they think that providers can access and modify some confidential data such as bank accounts. Many works have been done in this context, they conclude that encryption methods realized by providers ensure the confidentiality, but, they forgot that Cloud providers can decrypt the confidential resources. The best solution here is to apply some operations on the data before sending them to the provider Cloud in the objective to make them unreadable. The principal idea is to allow user how it can protect his data with his own methods. In this paper, we are going to demonstrate our approach and prove that is more efficient in term of execution time than some existing methods. This work aims at enhancing the quality of service of providers and ensuring the trust of the customers.
Abstract: In this paper we propose a computer-aided solution
with Genetic Algorithms in order to reduce the drafting of reports:
FMEA analysis and Control Plan required in the manufacture of the
product launch and improved knowledge development teams for
future projects. The solution allows to the design team to introduce
data entry required to FMEA. The actual analysis is performed using
Genetic Algorithms to find optimum between RPN risk factor and
cost of production. A feature of Genetic Algorithms is that they are
used as a means of finding solutions for multi criteria optimization
problems. In our case, along with three specific FMEA risk factors is
considered and reduce production cost. Analysis tool will generate
final reports for all FMEA processes. The data obtained in FMEA
reports are automatically integrated with other entered parameters in
Control Plan. Implementation of the solution is in the form of an
application running in an intranet on two servers: one containing
analysis and plan generation engine and the other containing the
database where the initial parameters and results are stored. The
results can then be used as starting solutions in the synthesis of other
projects. The solution was applied to welding processes, laser cutting
and bending to manufacture chassis for buses. Advantages of the
solution are efficient elaboration of documents in the current project
by automatically generating reports FMEA and Control Plan using
multiple criteria optimization of production and build a solid
knowledge base for future projects. The solution which we propose is
a cheap alternative to other solutions on the market using Open
Source tools in implementation.
Abstract: It is the worldwide problem that the recycled PVB is
not recycled and it is wildly stored in landfills. However, PVB has
similar chemical properties such as PVC. Moreover, both of these
polymers are plasticized. Therefore, the study of thermal properties
of plasticized PVC and the recycled PVB obtained by recycling of
windshields is carried out. This work has done in order to find nondegradable
processing conditions applicable for both polymers.
Tested PVC contained 38% of plasticizer diisononyl phthalate
(DINP) and PVB was plasticized with 28% of triethylene glycol,
bis(2-ethylhexanoate) (3GO). The thermal and thermo-oxidative
decomposition of both vinyl polymers are compared by calorimetric
analysis and by tensile strength analysis.
Abstract: Thousands of organisations store important and
confidential information related to them, their customers, and their
business partners in databases all across the world. The stored data
ranges from less sensitive (e.g. first name, last name, date of birth) to
more sensitive data (e.g. password, pin code, and credit card
information). Losing data, disclosing confidential information or
even changing the value of data are the severe damages that
Structured Query Language injection (SQLi) attack can cause on a
given database. It is a code injection technique where malicious SQL
statements are inserted into a given SQL database by simply using a
web browser. In this paper, we propose an effective pattern
recognition neural network model for detection and classification of
SQLi attacks. The proposed model is built from three main elements
of: a Uniform Resource Locator (URL) generator in order to generate
thousands of malicious and benign URLs, a URL classifier in order
to: 1) classify each generated URL to either a benign URL or a
malicious URL and 2) classify the malicious URLs into different
SQLi attack categories, and a NN model in order to: 1) detect either a
given URL is a malicious URL or a benign URL and 2) identify the
type of SQLi attack for each malicious URL. The model is first
trained and then evaluated by employing thousands of benign and
malicious URLs. The results of the experiments are presented in
order to demonstrate the effectiveness of the proposed approach.
Abstract: This paper discusses the design and analysis of a
hybrid PV-Fuel cell energy system destined to power a DC load. The
system is composed of a photovoltaic array, a fuel cell, an
electrolyzer and a hydrogen tank. HOMER software is used in this
study to calculate the optimum capacities of the power system
components that their combination allows an efficient use of solar
resource to cover the hourly load needs. The optimal system sizing
allows establishing the right balance between the daily electrical
energy produced by the power system and the daily electrical energy
consumed by the DC load using a 28 KW PV array, a 7.5 KW fuel
cell, a 40KW electrolyzer and a 270 Kg hydrogen tank. The variation
of powers involved into the DC bus of the hybrid PV-fuel cell system
has been computed and analyzed for each hour over one year: the
output powers of the PV array and the fuel cell, the input power of
the elctrolyzer system and the DC primary load. Equally, the annual
variation of stored hydrogen produced by the electrolyzer has been
assessed. The PV array contributes in the power system with 82%
whereas the fuel cell produces 18%. 38% of the total energy
consumption belongs to the DC primary load while the rest goes to
the electrolyzer.
Abstract: A large amount of data is typically stored in relational
databases (DB). The latter can efficiently handle user queries which
intend to elicit the appropriate information from data sources.
However, direct access and use of this data requires the end users to
have an adequate technical background, while they should also cope
with the internal data structure and values presented. Consequently
the information retrieval is a quite difficult process even for IT or DB
experts, taking into account the limited contributions of relational
databases from the conceptual point of view. Ontologies enable users
to formally describe a domain of knowledge in terms of concepts and
relations among them and hence they can be used for unambiguously
specifying the information captured by the relational database.
However, accessing information residing in a database using
ontologies is feasible, provided that the users are keen on using
semantic web technologies. For enabling users form different
disciplines to retrieve the appropriate data, the design of a Graphical
User Interface is necessary. In this work, we will present an
interactive, ontology-based, semantically enable web tool that can be
used for information retrieval purposes. The tool is totally based on
the ontological representation of underlying database schema while it
provides a user friendly environment through which the users can
graphically form and execute their queries.
Abstract: Load modeling is one of the central functions in
power systems operations. Electricity cannot be stored, which means
that for electric utility, the estimate of the future demand is necessary
in managing the production and purchasing in an economically
reasonable way. A majority of the recently reported approaches are
based on neural network. The attraction of the methods lies in the
assumption that neural networks are able to learn properties of the
load. However, the development of the methods is not finished, and
the lack of comparative results on different model variations is a
problem. This paper presents a new approach in order to predict the
Tunisia daily peak load. The proposed method employs a
computational intelligence scheme based on the Fuzzy neural
network (FNN) and support vector regression (SVR). Experimental
results obtained indicate that our proposed FNN-SVR technique gives
significantly good prediction accuracy compared to some classical
techniques.
Abstract: Ocimum americanum L (Lamiaceae) is an annual herb
that is native to tropical Africa. The in vitro and in vivo antioxidant
activity of its aqueous extract was carefully investigated by assessing
the DPPH radical scavenging activity, ABTS radical scavenging
activity and hydrogen peroxide radical scavenging activity. The
reducing power, total phenol, total flavonoids and flavonols content
of the extract were also evaluated. The data obtained revealed that the
extract is rich in polyphenolic compounds and scavenged the radicals
in a concentration dependent manner. This was done in comparison
with the standard antioxidants such as BHT and Vitamin C. Also, the
induction of oxidative damage with paracetamol (2000 mg/kg)
resulted in the elevation of lipid peroxides and significant (P < 0.05)
decrease in activities of superoxide dismutase, glutathione
peroxidase, glutathione reductase and catalase in the liver and kidney
of rats. However, the pretreatment of rats with aqueous extract of O.
americanum leaves (200 and 400 mg/kg) and silymarin (100 mg/kg)
caused a significant (P < 0.05) reduction in the values of lipid
peroxides and restored the levels of antioxidant parameters in these
organs. These findings suggest that the leaves of O. americanum have
potent antioxidant properties which may be responsible for its
acclaimed folkloric uses.