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: Although, arsenic trioxide has been the subject of
toxicological research, in vitro cytotoxicity and genotoxicity studies
using relevant cell models and uniform methodology are not well
elucidated. Hence, the aim of the present study was to evaluate the
cytotoxicity and genotoxicity induced by arsenic trioxide in human
keratinocytes (HaCaT) using the MTT [3-(4, 5-dimethylthiazol-2-yl)-
2,5-diphenyltetrazolium bromide] and alkaline single cell gel
electrophoresis (Comet) assays, respectively. Human keratinocytes
were treated with different doses of arsenic trioxide for 4 h prior to
cytogenetic assessment. Data obtained from the MTT assay indicated
that arsenic trioxide significantly reduced the viability of HaCaT cells
in a dose-dependent manner, showing an IC50 value of 34.18 ± 0.6
μM. Data generated from the comet assay also indicated a significant
dose-dependent increase in DNA damage in HaCaT cells associated
with arsenic trioxide exposure. We observed a significant increase in
comet tail length and tail moment, showing an evidence of arsenic
trioxide -induced genotoxic damage in HaCaT cells. This study
confirms that the comet assay is a sensitive and effective method to
detect DNA damage caused by arsenic.
Abstract: An experiment was conducted to determine the effect
of pollination on seed quality of rapeseed in Chitwan, Nepal during
2012-2013. The experiment was designed in Randomized Complete
Block with four replications and five treatments. The rapeseed plots
were caged with mosquito nets at 10% flowering except natural
pollination. Two-framed colonies of Apis mellifera L. and Apis
cerana F. were introduced separately for pollination, and control plot
caged without pollinators. The highest germination percent was
observed on Apis cerana F. pollinated plot seeds (90.50%
germination) followed by Apis mellifera L. pollinated plots (87.25 %)
and lowest on control plots (42.00% germination) seeds. Similarly,
seed test weight of Apis cerana F. pollinated plots (3.22 gm/ 1000
seed) and Apis mellifera L. pollinated plots (2.93 gm/1000 seed) were
and lowest on control plots (2.26 gm/ 1000 seed) recorded. Likewise,
oil content was recorded highest on pollinated by Apis cerana F.
(36.1%) followed by pollinated by Apis mellifera L. (35.4%) and
lowest on control plots (32.8%). This study clearly indicated
pollination increases the seed quality of rapeseed and therefore,
management of honeybee is necessary for producing higher quality of
rapeseed under Chitwan condition.
Abstract: Neurons in the nervous system communicate with
each other by producing electrical signals called spikes. To
investigate the physiological function of nervous system it is essential
to study the activity of neurons by detecting and sorting spikes in the
recorded signal. In this paper a method is proposed for considering
the spike sorting problem which is based on the nonlinear modeling
of spikes using exponential autoregressive model. The genetic
algorithm is utilized for model parameter estimation. In this regard
some selected model coefficients are used as features for sorting
purposes. For optimal selection of model coefficients, self-organizing
feature map is used. The results show that modeling of spikes with
nonlinear autoregressive model outperforms its linear counterpart.
Also the extracted features based on the coefficients of exponential
autoregressive model are better than wavelet based extracted features
and get more compact and well-separated clusters. In the case of
spikes different in small-scale structures where principal component
analysis fails to get separated clouds in the feature space, the
proposed method can obtain well-separated cluster which removes
the necessity of applying complex classifiers.
Abstract: The distribution networks are often exposed to harmful
incidents which can halt the electricity supply of the customer. In this
context, we studied a real case of a critical zone of the Tunisian
network which is currently characterized by the dysfunction of its
plan of protection. In this paper, we were interested in the
harmonization of the protection plan settings in order to ensure a
perfect selectivity and a better continuity of service on the whole of
the network.
Abstract: Urban areas have been expanded throughout the
globe. Monitoring and modelling urban growth have become a
necessity for a sustainable urban planning and decision making.
Urban prediction models are important tools for analyzing the causes
and consequences of urban land use dynamics. The objective of this
research paper is to analyze and model the urban change, which has
been occurred from 1990 to 2000 using CORINE land cover maps.
The model was developed using drivers of urban changes (such as
road distance, slope, etc.) under an Artificial Neural Network
modelling approach. Validation was achieved using a prediction map
for 2006 which was compared with a real map of Urban Atlas of
2006. The accuracy produced a Kappa index of agreement of 0,639
and a value of Cramer's V of 0,648. These encouraging results
indicate the importance of the developed urban growth prediction
model which using a set of available common biophysical drivers
could serve as a management tool for the assessment of urban
change.
Abstract: Currently, there is excessively growing information
about places on Facebook, which is the largest social network but
such information is not explicitly organized and ranked. Therefore
users cannot exploit such data to recommend places conveniently and
quickly. This paper proposes a Facebook application and an Android
application that recommend places based on the number of check-ins
of those places, the distance of those places from the current location,
the number of people who like Facebook page of those places, and
the number of talking about of those places. Related Facebook data is
gathered via Facebook API requests. The experimental results of the
developed applications show that the applications can recommend
places and rank interesting places from the most to the least. We have
found that the average satisfied score of the proposed Facebook
application is 4.8 out of 5. The users’ satisfaction can increase by
adding the app features that support personalization in terms of
interests and preferences.
Abstract: The dielectric properties and ionic conductivity of
novel "ceramic state" polymer electrolytes for high capacity lithium
battery are characterized by Radio frequency and Microwave
methods in two broad frequency ranges from 50 Hz to 20 KHz and 4
GHz to 40 GHz. This innovative solid polymer electrolyte which is
highly ionic conductive (10-3 S/cm at room temperature) from -40oC
to +150oC can be used in any battery application. Such polymer
exhibits properties more like a ceramic rather than polymer. The
various applied measurement methods produced accurate dielectric
results for comprehensive analysis of electrochemical properties and
ion transportation mechanism of this newly invented polymer
electrolyte. Two techniques and instruments employing air gap
measurement by Capacitance Bridge and in-waveguide measurement
by vector network analyzer are applied to measure the complex
dielectric spectra. The complex dielectric spectra are used to
determine the complex alternating current electrical conductivity and
thus the ionic conductivity.
Abstract: One image is worth more than thousand words.
Images if analyzed can reveal useful information. Low level image
processing deals with the extraction of specific feature from a single
image. Now the question arises: What technique should be used to
extract patterns of very large and detailed image database? The
answer of the question is: “Image Mining”. Image Mining deals with
the extraction of image data relationship, implicit knowledge, and
another pattern from the collection of images or image database. It is
nothing but the extension of Data Mining. In the following paper, not
only we are going to scrutinize the current techniques of image
mining but also present a new technique for mining images using
Genetic Algorithm.
Abstract: Early detection of breast cancer saves many thousands
of lives each year via application of mammography and genetic
screening and many more lives could be saved if nurses are involved
in breast care screening practices. So, the aim of the study was to
identify nurse's role in early detection of breast cancer through
mammography and genetic screening and its impact on patient's
outcome. In order to achieve this aim, 400 women above 40 years,
asymptomatic were recruited for mammography and genetic
screening. In addition, 50 nurses and 6 technologists were involved in
the study. A descriptive analytical design was used. Five tools were
utilized: sociodemographic, mammographic examination and risk
factors, women's before, during and after mammography, items
relaying to technologists, and items related to nurses were also
obtained. The study finding revealed that 3% of women detected for
malignancy and 7.25% for fibroadenoma. Statistically significant
differences were found between mammography results and age,
family history, genetic screening, exposure to smoke, and using
contraceptive pills. Nurses have insufficient knowledge about
screening tests. Based on these findings the present study
recommended involvement of nurses in breast care which is very
important to in force population about screening practices.
Abstract: The Standard Penetration Test (SPT) is the most
common in situ test for soil investigations. On the other hand, the
Cone Penetration Test (CPT) is considered one of the best
investigation tools. Due to the fast and accurate results that can be
obtained it complaints the SPT in many applications like field
explorations, design parameters, and quality control assessments.
Many soil index and engineering properties have been correlated to
both of SPT and CPT. Various foundation design methods were
developed based on the outcome of these tests. Therefore it is vital to
correlate these tests to each other so that either one of the tests can be
used in the absence of the other, especially for preliminary evaluation
and design purposes.
The primary purpose of this study was to investigate the
relationships between the SPT and CPT for different type of sandy
soils in Florida. Data for this research were collected from number of
projects sponsored by the Florida Department of Transportation
(FDOT), six sites served as the subject of SPT-CPT correlations. The
correlations were established between the cone resistance (qc), sleeve
friction (fs) and the uncorrected SPT blow counts (N) for various
soils.
A positive linear relationship was found between qc, fs and N for
various sandy soils. In general, qc versus N showed higher
correlation coefficients than fs versus N. qc/N ratios were developed
for different soil types and compared to literature values, the results
of this research revealed higher ratios than literature values.
Abstract: The use of technology in the classroom is an issue that
is constantly evolving. Digital age students learn differently than their
teachers did, so now the teacher should be constantly evolving their
methods and teaching techniques to be more in touch with the
student. In this paper a case study presents how were used some of
these technologies by accompanying a classroom course, this in order
to provide students with a different and innovative experience as their
teacher usually presented the activities to develop. As students
worked in the various activities, they increased their digital skills by
employing unknown tools that helped them in their professional
training. The twenty-first century teacher should consider the use of
Information and Communication Technologies in the classroom
thinking in skills that students of the digital age should possess. It
also takes a brief look at the history of distance education and it is
also highlighted the importance of integrating technology as part of
the student's training.
Abstract: The present paper summarizes the analysis of the
request for consultation of information and data on industrial
emissions made publicly available on the web site of the Ministry of
Environment, Land and Sea on integrated pollution prevention and
control from large industrial installations, the so called “AIA Portal”.
As a matter of fact, a huge amount of information on national
industrial plants is already available on internet, although it is usually
proposed as textual documentation or images.
Thus, it is not possible to access all the relevant information
through interoperability systems and also to retrieval relevant
information for decision making purposes as well as rising of
awareness on environmental issue.
Moreover, since in Italy the number of institutional and private
subjects involved in the management of the public information on
industrial emissions is substantial, the access to the information is
provided on internet web sites according to different criteria; thus, at
present it is not structurally homogeneous and comparable.
To overcome the mentioned difficulties in the case of the
Coordinating Committee for the implementation of the Agreement
for the industrial area in Taranto and Statte, operating before the
IPPC permit granting procedures of the relevant installation located
in the area, a big effort was devoted to elaborate and to validate data
and information on characterization of soil, ground water aquifer and
coastal sea at disposal of different subjects to derive a global
perspective for decision making purposes. Thus, the present paper
also focuses on main outcomes matured during such experience.
Abstract: An analysis is carried out to investigate the effect of
magnetic field and heat source on the steady boundary layer flow and
heat transfer of a Casson nanofluid over a vertical cylinder stretching
exponentially along its radial direction. Using a similarity
transformation, the governing mathematical equations, with the
boundary conditions are reduced to a system of coupled, non –linear
ordinary differential equations. The resulting system is solved
numerically by the fourth order Runge – Kutta scheme with shooting
technique. The influence of various physical parameters such as
Reynolds number, Prandtl number, magnetic field, Brownian motion
parameter, thermophoresis parameter, Lewis number and the natural
convection parameter are presented graphically and discussed for non
– dimensional velocity, temperature and nanoparticle volume
fraction. Numerical data for the skin – friction coefficient, local
Nusselt number and the local Sherwood number have been tabulated
for various parametric conditions. It is found that the local Nusselt
number is a decreasing function of Brownian motion parameter Nb
and the thermophoresis parameter Nt.
Abstract: Verification and Validation of Simulated Process
Model is the most important phase of the simulator life cycle.
Evaluation of simulated process models based on Verification and
Validation techniques checks the closeness of each component model
(in a simulated network) with the real system/process with respect to
dynamic behaviour under steady state and transient conditions. The
process of Verification and Validation helps in qualifying the process
simulator for the intended purpose whether it is for providing
comprehensive training or design verification. In general, model
verification is carried out by comparison of simulated component
characteristics with the original requirement to ensure that each step
in the model development process completely incorporates all the
design requirements. Validation testing is performed by comparing
the simulated process parameters to the actual plant process
parameters either in standalone mode or integrated mode.
A Full Scope Replica Operator Training Simulator for PFBR -
Prototype Fast Breeder Reactor has been developed at IGCAR,
Kalpakkam, INDIA named KALBR-SIM (Kalpakkam Breeder
Reactor Simulator) where in the main participants are
engineers/experts belonging to Modeling Team, Process Design and
Instrumentation & Control design team. This paper discusses about
the Verification and Validation process in general, the evaluation
procedure adopted for PFBR operator training Simulator, the
methodology followed for verifying the models, the reference
documents and standards used etc. It details out the importance of
internal validation by design experts, subsequent validation by
external agency consisting of experts from various fields, model
improvement by tuning based on expert’s comments, final
qualification of the simulator for the intended purpose and the
difficulties faced while co-coordinating various activities.
Abstract: This study is concerned with the optimization of
fermentation parameters for the hyper production of mannanase from
Fusarium oxysporum SS-25 employing two step statistical strategy
and kinetic characterization of crude enzyme preparation. The
Plackett-Burman design used to screen out the important factors in
the culture medium revealed 20% (w/w) wheat bran, 2% (w/w) each
of potato peels, soyabean meal and malt extract, 1% tryptone, 0.14%
NH4SO4, 0.2% KH2PO4, 0.0002% ZnSO4, 0.0005% FeSO4, 0.01%
MnSO4, 0.012% SDS, 0.03% NH4Cl, 0.1% NaNO3 in brewer’s spent
grain based medium with 50% moisture content, inoculated with
2.8×107 spores and incubated at 30oC for 6 days to be the main
parameters influencing the enzyme production. Of these factors, four
variables including soyabean meal, FeSO4, MnSO4 and NaNO3 were
chosen to study the interactive effects and their optimum levels in
central composite design of response surface methodology with the
final mannanase yield of 193 IU/gds. The kinetic characterization
revealed the crude enzyme to be active over broader temperature and
pH range. This could result in 26.6% reduction in kappa number with
4.93% higher tear index and 1% increase in brightness when used to
treat the wheat straw based kraft pulp. The hydrolytic potential of
enzyme was also demonstrated on both locust bean gum and guar
gum.
Abstract: Advanced head and neck cancers are aggressive
tumours, which require aggressive treatment. Treatment efficiency is
often hindered by cancer cell repopulation during radiotherapy,
which is due to various mechanisms triggered by the loss of tumour
cells and involves both stem and differentiated cells. The aim of the
current paper is to present in silico simulations of radiotherapy
schedules on a virtual head and neck tumour grown with biologically
realistic kinetic parameters. Using the linear quadratic formalism of
cell survival after radiotherapy, altered fractionation schedules
employing various treatment breaks for normal tissue recovery are
simulated and repopulation mechanism implemented in order to
evaluate the impact of various cancer cell contribution on tumour
behaviour during irradiation. The model has shown that the timing of
treatment breaks is an important factor influencing tumour control in
rapidly proliferating tissues such as squamous cell carcinomas of the
head and neck. Furthermore, not only stem cells but also
differentiated cells, via the mechanism of abortive division, can
contribute to malignant cell repopulation during treatment.
Abstract: The emerging Cognitive Radio is combo of both the
technologies i.e. Radio dynamics and software technology. It involve
wireless system with efficient coding, designing, and making them
artificial intelligent to take the decision according to the surrounding
environment and adopt themselves accordingly, so as to deliver the
best QoS. This is the breakthrough from fixed hardware and fixed
utilization of the spectrum. This software-defined approach of
research is centralized at user-definition and application driven
model, various software method are used for the optimization of the
wireless communication. This paper focused on the Spectrum
allocation technique using genetic algorithm GA to evolve radio,
represented by chromosomes. The chromosomes gene represents the
adjustable parameters in given radio and by using GA, evolving over
the generations, the optimized set of parameters are evolved, as per
the requirement of user and availability of the spectrum, in our
prototype the gene consist of 6 different parameters, and the best set
of parameters are evolved according to the application need and
availability of the spectrum holes and thus maintaining best QoS for
user, simultaneously maintaining licensed user rights. The analyzing
tool Matlab is used for the performance of the prototype.
Abstract: Different tools and technologies were implemented
for Crisis Response and Management (CRM) which is generally
using available network infrastructure for information exchange.
Depending on type of disaster or crisis, network infrastructure could
be affected and it could not be able to provide reliable connectivity.
Thus any tool or technology that depends on the connectivity could
not be able to fulfill its functionalities. As a solution, a new message
exchange framework has been developed. Framework provides
offline/online information exchange platform for CRM Information
Systems (CRMIS) and it uses XML compression and packet
prioritization algorithms and is based on open source web
technologies. By introducing offline capabilities to the web
technologies, framework will be able to perform message exchange
on unreliable networks. The experiments done on the simulation
environment provide promising results on low bandwidth networks
(56kbps and 28.8 kbps) with up to 50% packet loss and the solution is
to successfully transfer all the information on these low quality
networks where the traditional 2 and 3 tier applications failed.
Abstract: Eucalyptus species are well reputed for their
traditional use in Asia as well as in other parts of the world; therefore,
the present study was designed to investigate the antimicrobial and
antioxidant activities associated with essential oils from different
Eucalyptus species. Essential oils from the leaves of six Eucalyptus
species, including: Eucalyptus woodwardi, Eucalyptus stricklandii,
Eucalyptus salubris, Eucalyptus sargentii, Eucalyptus torquata and
Eucalyptus wandoo were separated by hydrodistillation and dried
over anhydrous sodium sulphate. DPPH, ferric reducing antioxidant
power, and hydroxyl radical scavenging activity assays were carried
out to evaluate the antioxidant potential of the oils. The results
indicate that examined oils exhibit substantial antioxidant activities
relative to ascorbic acid. Previously, these oils were evaluated for
their antimicrobial activities, against wide range of bacterial and
fungal strains, and they were shown to possess significant
antimicrobial activities. In this study, further investigation into the
growth kinetics of oil-treated microbial cultures was conducted. The
results clearly demonstrate that the microbial growth was markedly
inhibited when treated with sub-MIC concentrations of the oils.
Taken together, the results obtained indicate a high potential of the
examined essential oils as bioactive oils, for nutraceutical and
medical applications, possessing significant antioxidant and anti
microbial activities.