Abstract: Estimation of model parameters is necessary to predict
the behavior of a system. Model parameters are estimated using
optimization criteria. Most algorithms use historical data to estimate
model parameters. The known target values (actual) and the output
produced by the model are compared. The differences between the
two form the basis to estimate the parameters. In order to compare
different models developed using the same data different criteria are
used. The data obtained for short scale projects are used here. We
consider software effort estimation problem using radial basis
function network. The accuracy comparison is made using various
existing criteria for one and two predictors. Then, we propose a new
criterion based on linear least squares for evaluation and compared
the results of one and two predictors. We have considered another
data set and evaluated prediction accuracy using the new criterion.
The new criterion is easy to comprehend compared to single statistic.
Although software effort estimation is considered, this method is
applicable for any modeling and prediction.
Abstract: Biofuels production has come forth as a future
technology to combat the problem of depleting fossil fuels. Bio-based
ethanol production from enzymatic lignocellulosic biomass
degradation serves an efficient method and catching the eye of
scientific community. High cost of the enzyme is the major obstacle
in preventing the commercialization of this process. Thus main
objective of the present study was to optimize composition of
medium components for enhancing cellulase production by newly
isolated strain of Bacillus tequilensis. Nineteen factors were taken
into account using statistical Plackett-Burman Design. The significant
variables influencing the cellulose production were further employed
in statistical Response Surface Methodology using Central
Composite Design for maximizing cellulase production. The
optimum medium composition for cellulase production was: peptone
(4.94 g/L), ammonium chloride (4.99 g/L), yeast extract (2.00 g/L),
Tween-20 (0.53 g/L), calcium chloride (0.20 g/L) and cobalt chloride
(0.60 g/L) with pH 7, agitation speed 150 rpm and 72 h incubation at
37oC. Analysis of variance (ANOVA) revealed high coefficient of
determination (R2) of 0.99. Maximum cellulase productivity of 11.5
IU/ml was observed against the model predicted value of 13 IU/ml.
This was found to be optimally active at 60oC and pH 5.5.
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: Cell volume, together with membrane potential and
intracellular hydrogen ion concentration, is an essential biophysical
parameter for normal cellular activity. Cell volumes can be altered by
osmotically active compounds and extracellular tonicity.
In this study, a simple mathematical model of osmotically induced
cell swelling and shrinking is presented. Emphasis is given to water
diffusion across the membrane. The mathematical description of the
cellular behavior consists in a system of coupled ordinary differential
equations. We compare experimental data of cell volume alterations
driven by differences in osmotic pressure with mathematical
simulations under hypotonic and hypertonic conditions. Implications
for a future model are also discussed.
Abstract: Graphical User Interface (GUI) is essential to
programming, as is any other characteristic or feature, due to the fact
that GUI components provide the fundamental interaction between
the user and the program. Thus, we must give more interest to GUI
during building and development of systems. Also, we must give a
greater attention to the user who is the basic corner in the dealing
with the GUI. This paper introduces an approach for designing GUI
from one of the models of business workflows which describe the
workflow behavior of a system, specifically through Activity
Diagrams (AD).
Abstract: As the use of geothermal energy grows internationally
more effort is required to monitor and protect areas with rare and
important geothermal surface features. A number of approaches are
presented for developing and calibrating numerical geothermal
reservoir models that are capable of accurately representing
geothermal surface features. The approaches are discussed in the
context of cases studies of the Rotorua geothermal system and the
Orakei-korako geothermal system, both of which contain important
surface features. The results show that models are able to match the
available field data accurately and hence can be used as valuable
tools for predicting the future response of the systems to changes in
use.
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: Random epistemologies and hash tables have garnered
minimal interest from both security experts and experts in the last
several years. In fact, few information theorists would disagree with
the evaluation of expert systems. In our research, we discover how
flip-flop gates can be applied to the study of superpages. Though
such a hypothesis at first glance seems perverse, it is derived from
known results.
Abstract: For the treatment of acute and chronic lung diseases it is preferred to deliver medicaments by inhalation. The drug is delivered directly to tracheobronchial tree. This way allows the given medicament to get directly into the place of action and it makes rapid onset of action and maximum efficiency. The transport of aerosol particles in the particular part of the lung is influenced by their size, anatomy of the lungs, breathing pattern and airway resistance. This article deals with calculation of airway resistance in the lung model of Horsfield. It solves the problem of determination of the pressure losses in bifurcation and thus defines the pressure drop at a given location in the bronchial tree. The obtained data will be used as boundary conditions for transport of aerosol particles in a central part of bronchial tree realized by Computational Fluid Dynamics (CFD) approach. The results obtained from CFD simulation will allow us to provide information on the required particle size and optimal inhalation technique for particle transport into particular part of the lung.
Abstract: The 3D body movement signals captured during
human-human conversation include clues not only to the content of
people’s communication but also to their culture and personality.
This paper is concerned with automatic extraction of this information
from body movement signals. For the purpose of this research, we
collected a novel corpus from 27 subjects, arranged them into groups
according to their culture. We arranged each group into pairs and
each pair communicated with each other about different topics.
A state-of-art recognition system is applied to the problems of
person, culture, and topic recognition. We borrowed modeling,
classification, and normalization techniques from speech recognition.
We used Gaussian Mixture Modeling (GMM) as the main technique
for building our three systems, obtaining 77.78%, 55.47%, and
39.06% from the person, culture, and topic recognition systems
respectively. In addition, we combined the above GMM systems with
Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and
40.63% accuracy for person, culture, and topic recognition
respectively.
Although direct comparison among these three recognition
systems is difficult, it seems that our person recognition system
performs best for both GMM and GMM-SVM, suggesting that intersubject
differences (i.e. subject’s personality traits) are a major
source of variation. When removing these traits from culture and
topic recognition systems using the Nuisance Attribute Projection
(NAP) and the Intersession Variability Compensation (ISVC)
techniques, we obtained 73.44% and 46.09% accuracy from culture
and topic recognition systems respectively.
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: Diffusion stills have been effective in water
desalination. The present work represents a model of the distillation
process by using vertical single-effect diffusion stills. A semianalytical
model has been developed to model the process. A
software computer code using Engineering Equation Solver EES
software has been developed to solve the equations of the developed
model. An experimental setup has been constructed, and used for the
validation of the model. The model is also validated against former
literature results. The results obtained from the present experimental
test rig, and the data from the literature, have been compared with the
results of the code to find its best range of validity. In addition, a
parametric analysis of the system has been developed using the
model to determine the effect of operating conditions on the system's
performance. The dominant parameters that affect the productivity of
the still are the hot plate temperature that ranges from (55- 90°C) and
feed flow rate in range of (0.00694-0.0211 kg/m2-s).
Abstract: PLA emerged as a promising polymer because of its
property as a compostable, biodegradable thermoplastic made from
renewable sources. PLA can be polymerized from monomers
(Lactide or Lactic acid) obtained by fermentation processes from
renewable sources such as corn starch or sugarcane. For PLA
synthesis, ring opening polymerization (ROP) of Lactide monomer is
one of the preferred methods. In the literature, the technique mainly
developed for ROP of PLA is based on metal/bimetallic catalyst (Sn,
Zn and Al) or other organic catalysts in suitable solvent. However,
the PLA synthesized using such catalysts may contain trace elements
of the catalyst which may cause toxicity. This work estimated the
usefulness and drawbacks of using different catalysts as well as effect
of alternative energies and future aspects for PLA production.
Abstract: Geometric and mechanical properties all influence the
resistance of RC structures and may, in certain combination of
property values, increase the risk of a brittle failure of the whole
system.
This paper presents a statistical and probabilistic investigation on
the resistance of RC beams designed according to Eurocodes 2 and 8,
and subjected to multiple failure modes, under both the natural
variation of material properties and the uncertainty associated with
cross-section and transverse reinforcement geometry. A full
probabilistic model based on JCSS Probabilistic Model Code is
derived. Different beams are studied through material nonlinear
analysis via Monte Carlo simulations. The resistance model is
consistent with Eurocode 2. Both a multivariate statistical evaluation
and the data clustering analysis of outcomes are then performed.
Results show that the ultimate load behaviour of RC beams
subjected to flexural and shear failure modes seems to be mainly
influenced by the combination of the mechanical properties of both
longitudinal reinforcement and stirrups, and the tensile strength of
concrete, of which the latter appears to affect the overall response of
the system in a nonlinear way. The model uncertainty of the
resistance model used in the analysis plays undoubtedly an important
role in interpreting results.
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: These days, the field of tissue engineering is getting
serious attention due to its usefulness. Bone tissue engineering helps
to address and sort-out the critical sized and non-healing orthopedic
problems by the creation of manmade bone tissue. We will design
and validate an efficient numerical model, which will simulate the
effective diffusivity in bone tissue engineering. Our numerical model
will be based on the finite element analysis of the diffusion-reaction
equations. It will have the ability to optimize the diffusivity, even
at multi-scale, with the variation of time. It will also have a special
feature “parametric sweep”, with which we will be able to predict
the oxygen, glucose and cell density dynamics, more accurately. We
will fix these problems by modifying the governing equations, by
selecting appropriate spatio-temporal finite element schemes and by
transient analysis.
Abstract: Since columns are the most important elements of the
structures, failure of one column in a critical location can cause a
progressive collapse. In this respect, the repair and strengthening of
columns is a very important subject to reduce the building failure and
to keep the columns capacity. Twenty columns with different
parameters is tested and analysis. Eleven typical confined reinforced
concrete (RC) columns with different types of techniques are
assessment. And also, four confined concrete columns with plastic
tube (PVC) are tested with and with four paralleling tested of
unconfined plain concrete. The techniques of confined RC columns
are mortar strengthening, Steel rings strengthening, FRP
strengthening. Moreover, the technique of confined plain concrete
(PC) column is used PVC tubes. The columns are tested under
uniaxial compressive loads studied the effect of confinement on the
structural behavior of circular RC columns. Test results for each
column are presented in the form of crack patterns, stress-strain
curves. Test results show that confining of the RC columns using
different techniques of strengthening results significant improvement
of the general behavior of the columns and can used in construction.
And also, tested confined PC columns with PVC tubes results shown
that the confined PC with PVC tubes can be used in economical
building. The theoretical model for predicted column capacity is
founded with experimental factor depends on the confined techniques
used and the strain reduction.
Abstract: This study carried out comparative seismic
performance of reinforced concrete frames infilled by masonry walls
with different heights. Partial and fully infilled reinforced concrete
frames were modeled for the research objectives and the analysis
model for a bare reinforced concrete frame was also established for
comparison. Non–linear static analyses for the studied frames were
performed to investigate their structural behavior under extreme
seismic loads and to find out their collapse mechanism. It was
observed from analysis results that the strengths of the partial infilled
reinforced concrete frames are increased and their ductilities are
reduced, as infilled masonry walls are higher. Especially, reinforced
concrete frames with higher partial infilled masonry walls would
experience shear failures. Non–linear dynamic analyses using 10
earthquake records show that the bare and fully infilled reinforced
concrete frame present stable collapse mechanism while the reinforced
concrete frames with partially infilled masonry walls collapse in more
brittle manner due to short-column effects.
Abstract: Modelling of the earth's surface and evaluation of
urban environment, with 3D models, is an important research topic.
New stereo capabilities of high resolution optical satellites images,
such as the tri-stereo mode of Pleiades, combined with new image
matching algorithms, are now available and can be applied in urban
area analysis. In addition, photogrammetry software packages gained
new, more efficient matching algorithms, such as SGM, as well as
improved filters to deal with shadow areas, can achieve more dense
and more precise results.
This paper describes a comparison between 3D data extracted
from tri-stereo and dual stereo satellite images, combined with pixel
based matching and Wallis filter. The aim was to improve the
accuracy of 3D models especially in urban areas, in order to assess if
satellite images are appropriate for a rapid evaluation of urban
environments.
The results showed that 3D models achieved by Pleiades tri-stereo
outperformed, both in terms of accuracy and detail, the result
obtained from a Geo-eye pair. The assessment was made with
reference digital surface models derived from high resolution aerial
photography. This could mean that tri-stereo images can be
successfully used for the proposed urban change analyses.
Abstract: This research focused on comparing the critical
thinking of the teacher students before and after using Miller’s Model
learning activities and investigating their opinions. The sampling
groups were (1) fourth year 33 student teachers majoring in Early
Childhood Education and enrolling in semester 1 of academic year
2013 (2) third year 28 student teachers majoring in English and
enrolling in semester 2 of academic year 2013 and (3) third year 22
student teachers majoring in Thai and enrolling in semester 2 of
academic year 2013. The research instruments were (1) lesson plans
where the learning activities were settled based on Miller’s Model (2)
critical thinking assessment criteria and (3) a questionnaire on
opinions towards Miller’s Model based learning activities. The
statistical treatment was mean, deviation, different scores and T-test.
The result unfolded that (1) the critical thinking of the students after
the assigned activities was better than before and (2) the students’
opinions towards the critical thinking improvement activities based
on Miller’s Model ranged from the level of high to highest.