Abstract: Human beings have the ability to make logical
decisions. Although human decision - making is often optimal, it is
insufficient when huge amount of data is to be classified. Medical
dataset is a vital ingredient used in predicting patient’s health
condition. In other to have the best prediction, there calls for most
suitable machine learning algorithms. This work compared the
performance of Artificial Neural Network (ANN) and Decision Tree
Algorithms (DTA) as regards to some performance metrics using
diabetes data. WEKA software was used for the implementation of
the algorithms. Multilayer Perceptron (MLP) and Radial Basis
Function (RBF) were the two algorithms used for ANN, while
RegTree and LADTree algorithms were the DTA models used. From
the results obtained, DTA performed better than ANN. The Root
Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is
0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206
respectively.
Abstract: DNA Barcode provides good sources of needed
information to classify living species. The classification problem has
to be supported with reliable methods and algorithms. To analyze
species regions or entire genomes, it becomes necessary to use the
similarity sequence methods. A large set of sequences can be
simultaneously compared using Multiple Sequence Alignment which
is known to be NP-complete. However, all the used methods are still
computationally very expensive and require significant computational
infrastructure. Our goal is to build predictive models that are highly
accurate and interpretable. In fact, our method permits to avoid the
complex problem of form and structure in different classes of
organisms. The empirical data and their classification performances
are compared with other methods. Evenly, in this study, we present
our system which is consisted of three phases. The first one, is called
transformation, is composed of three sub steps; Electron-Ion
Interaction Pseudopotential (EIIP) for the codification of DNA
Barcodes, Fourier Transform and Power Spectrum Signal Processing.
Moreover, the second phase step is an approximation; it is
empowered by the use of Multi Library Wavelet Neural Networks
(MLWNN). Finally, the third one, is called the classification of DNA
Barcodes, is realized by applying the algorithm of hierarchical
classification.
Abstract: Nanotechnology has become the world attention in
various applications including the solar cells devices due to the
uniqueness and benefits of achieving low cost and better
performances of devices. Recently, thin film solar cells such as
Cadmium Telluride (CdTe), Copper-Indium-Gallium-diSelenide
(CIGS), Copper-Zinc-Tin-Sulphide (CZTS), and Dye-Sensitized
Solar Cells (DSSC) enhanced by nanotechnology have attracted
much attention. Thus, a compilation of nanotechnology devices
giving the progress in the solar cells has been presented. It is much
related to nanoparticles or nanocrystallines, carbon nanotubes, and
nanowires or nanorods structures.
Abstract: In this paper, we present a new segmentation approach
for liver lesions in regions of interest within MRI (Magnetic
Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans
methodology, considers the parameter variable compactness
to handle uncertainty. Fine boundaries are detected by a local
recursive merging of ambiguous pixels with a sequential forward
floating selection with Zernike moments. The method has been tested
on both synthetic and real images. When applied on synthetic images,
the proposed approach provides good performance, segmentations
obtained are accurate, their shape is consistent with the ground truth,
and the extracted information is reliable. The results obtained on MR
images confirm such observations. Our approach allows, even for
difficult cases of MR images, to extract a segmentation with good
performance in terms of accuracy and shape, which implies that the
geometry of the tumor is preserved for further clinical activities (such
as automatic extraction of pharmaco-kinetics properties, lesion
characterization, etc.).
Abstract: This work presents an improved single fiber pull-out
test for fiber/matrix interface characterization. This test has been
used to study the Inter-Facial Shear Strength ‘IFSS’ of hemp fibers
reinforced polypropylene (PP). For this aim, the fiber diameter
has been carefully measured using a tomography inspired method.
The fiber section contour can then be approximated by a circle
or a polygon. The results show that the IFSS is overestimated if
the circular approximation is used. The Influence of the molding
temperature on the IFSS has also been studied. We find that a molding
temperature of 183◦C leads to better interfacial properties. Above or
below this temperature the interface strength is reduced.
Abstract: Distillery spentwash contains high chemical oxygen
demand (COD), biological oxygen demand (BOD), color, total
dissolved solids (TDS) and other contaminants even after biological
treatment. The effluent can’t be discharged as such in the surface
water bodies or land without further treatment. Reverse osmosis (RO)
treatment plants have been installed in many of the distilleries at
tertiary level in many of the distilleries in India, but are not properly
working due to fouling problem which is caused by the presence of
high concentration of organic matter and other contaminants in
biologically treated spentwash. In order to make the membrane
treatment a proven and reliable technology, proper pre-treatment is
mandatory. In the present study, ultra-filtration (UF) for pretreatment
of RO at tertiary stage has been performed. Operating
parameters namely initial pH (pHo: 2–10), trans-membrane pressure
(TMP: 4-20 bars) and temperature (T: 15-43°C) were used for
conducting experiments with UF system. Experiments were
optimized at different operating parameters in terms of COD, color,
TDS and TOC removal by using response surface methodology
(RSM) with central composite design. The results showed that
removal of COD, color and TDS was 62%, 93.5% and 75.5%
respectively, with UF, at optimized conditions with increased
permeate flux from 17.5 l/m2/h (RO) to 38 l/m2/h (UF-RO). The
performance of the RO system was greatly improved both in term of
pollutant removal as well as water recovery.
Abstract: The economic use and ease of construction of profiled
deck composite slab is marred with the complex and un-economic
strength verification required for the serviceability and general safety
considerations. Beside these, albeit factors such as shear span length,
deck geometries and mechanical frictions greatly influence the
longitudinal shear strength, that determines the ultimate strength of
profiled deck composite slab, and number of methods available for its
determination; partial shear and slope-intercept are the two methods
according to Euro-code 4 provision. However, the complexity
associated with shear behavior of profiled deck composite slab, the
use of these methods in determining the load carrying capacities of
such slab yields different and conflicting values. This couple with the
time and cost constraint associated with the strength verification is a
source of concern that draws more attentions nowadays, the issue is
critical. Treating some of these known shear strength influencing
factors as random variables, the load carrying capacity violation of
profiled deck composite slab from the use of the two-methods
defined according to Euro-code 4 are determined using reliability
approach, and comparatively studied. The study reveals safety values
from the use of m-k method shows good standing compared with that
from the partial shear method.
Abstract: The aim of the present study is to detect the chaotic
behavior in monetary economic relevant dynamical system. The
study employs three different forms of Taylor rules: current, forward,
and backward looking. The result suggests the existence of the
chaotic behavior in all three systems. In addition, the results strongly
represent that using expectations in policy rule especially rational
expectation hypothesis can increase complexity of the system and
leads to more chaotic behavior.
Abstract: Bicycle Level of Service (BLOS) is a measure for
evaluating street conditions for cyclists. Currently, various methods
are proposed for BLOS. These analytical methods however have
some drawbacks: they usually assume cyclists as users that can share
street facilities with motorized vehicles, it is not easy to link them to
design process and they are not easy to follow. In addition, they only
support a narrow range of cycling facilities and may not be applicable
for all situations. Along this, the current paper introduces various
effective design factors for bicycle-friendly streets. This study
considers cyclists as users of streets who have special needs and
facilities. Therefore, the key factors that influence BLOS based on
different cycling facilities that are proposed by developed guidelines
and literature are identified. The combination of these factors
presents a complete set of effective design factors for bicycle-friendly
streets. In addition, the weight of each factor in existing BLOS
models is estimated and these effective factors are ranked based on
these weights. These factors and their weights can be used in further
studies to propose special bicycle-friendly street design model.
Abstract: We apply the non-parametric, unconditional,
hyperbolic order-α quantile estimator to appraise the relative
efficiency of Microfinance Institutions in Africa in terms of outreach.
Our purpose is to verify if these institutions, which must constantly
try to strike a compromise between their social role and financial
sustainability are operationally efficient.
Using data on African MFIs extracted from the Microfinance
Information eXchange (MIX) database and covering the 2004 to
2006 periods, we find that more efficient MFIs are also the most
profitable. This result is in line with the view that social performance
is not in contradiction with the pursuit of excellent financial
performance. Our results also show that large MFIs in terms of asset
and those charging the highest fees are not necessarily the most
efficient.
Abstract: This paper describes a new approach which can be
used to interpret the experimental creep deformation data obtained
from miniaturized thin plate bending specimen test to the
corresponding uniaxial data based on an inversed application of the
reference stress method. The geometry of the thin plate is fully
defined by the span of the support, l, the width, b, and the thickness,
d. Firstly, analytical solutions for the steady-state, load-line creep
deformation rate of the thin plates for a Norton’s power law under
plane stress (b→0) and plane strain (b→∞) conditions were obtained,
from which it can be seen that the load-line deformation rate of the
thin plate under plane-stress conditions is much higher than that
under the plane-strain conditions. Since analytical solution is not
available for the plates with random b-values, finite element (FE)
analyses are used to obtain the solutions. Based on the FE results
obtained for various b/l ratios and creep exponent, n, as well as the
analytical solutions under plane stress and plane strain conditions, an
approximate, numerical solutions for the deformation rate are
obtained by curve fitting. Using these solutions, a reference stress
method is utilised to establish the conversion relationships between
the applied load and the equivalent uniaxial stress and between the
creep deformations of thin plate and the equivalent uniaxial creep
strains. Finally, the accuracy of the empirical solution was assessed
by using a set of “theoretical” experimental data.
Abstract: Steepest descent method is a simple gradient method
for optimization. This method has a slow convergence in heading to
the optimal solution, which occurs because of the zigzag form of the
steps. Barzilai and Borwein modified this algorithm so that it
performs well for problems with large dimensions. Barzilai and
Borwein method results have sparked a lot of research on the method
of steepest descent, including alternate minimization gradient method
and Yuan method. Inspired by previous works, we modified the step
size of the steepest descent method. We then compare the
modification results against the Barzilai and Borwein method,
alternate minimization gradient method and Yuan method for
quadratic function cases in terms of the iterations number and the
running time. The average results indicate that the steepest descent
method with the new step sizes provide good results for small
dimensions and able to compete with the results of Barzilai and
Borwein method and the alternate minimization gradient method for
large dimensions. The new step sizes have faster convergence
compared to the other methods, especially for cases with large
dimensions.
Abstract: Artificial neural networks have gained a lot of interest
as empirical models for their powerful representational capacity,
multi input and output mapping characteristics. In fact, most feedforward
networks with nonlinear nodal functions have been proved to
be universal approximates. In this paper, we propose a new
supervised method for color image classification based on selforganizing
feature maps (SOFM). This algorithm is based on
competitive learning. The method partitions the input space using
self-organizing feature maps to introduce the concept of local
neighborhoods. Our image classification system entered into RGB
image. Experiments with simulated data showed that separability of
classes increased when increasing training time. In additional, the
result shows proposed algorithms are effective for color image
classification.
Abstract: Aurèsregion is one of the arid and semi-arid areas that
have suffered climate crises and overexploitation of natural resources
they have led to significant land degradation. The use of remote sensing data allowed us to analyze the land and
its spatiotemporal changes in the Aurès between 1987 and 2013, for
this work, we adopted a method of analysis based on the exploitation
of the images satellite Landsat TM 1987 and Landsat OLI 2013, from
the supervised classification likelihood coupled with field surveys of
the mission of May and September of 2013. Using ENVI EX software by the superposition of the ground cover
maps from 1987 and 2013, one can extract a spatial map change of
different land cover units. The results show that between 1987 and
2013 vegetation has suffered negative changes are the significant
degradation of forests and steppe rangelands, and sandy soils and
bare land recorded a considerable increase. The spatial change map land cover units between 1987 and 2013
allows us to understand the extensive or regressive orientation of
vegetation and soil, this map shows that dense forests give his place
to clear forests and steppe vegetation develops from a degraded forest
vegetation and bare, sandy soils earn big steppe surfaces that explain
its remarkable extension.
The analysis of remote sensing data highlights the profound
changes in our environment over time and quantitative monitoring of
the risk of desertification.
Abstract: Numerical investigations were conducted to study the
influence of flexural reinforcement ratio on the diagonal cracking
strength and ultimate shear strength of reinforced concrete (RC)
beams without stirrups. Three-dimensional nonlinear finite element
analyses (FEAs) of the beams with flexural reinforcement ratios
ranging from 0.58% to 2.20% subjected to a mid-span concentrated
load were carried out. It is observed that the load-deflection and loadstrain
curves obtained from the numerical analyses agree with those
obtained from the experiments. It is concluded that flexural
reinforcement ratio has a significant effect on the shear strength and
deflection capacity of RC beams without stirrups. The predictions of
diagonal cracking strength and ultimate shear strength of beams
obtained by using the equations defined by a number of codes and
researchers are compared with each other and with the experimental
values.
Abstract: This paper presents a state-of-the-art survey of the
operations research models developed for internal audit planning.
Two alternative approaches have been followed in the literature for
audit planning: (1) identifying the optimal audit frequency; and (2)
determining the optimal audit resource allocation. The first approach
identifies the elapsed time between two successive audits, which can
be presented as the optimal number of audits in a given planning
horizon, or the optimal number of transactions after which an audit
should be performed. It also includes the optimal audit schedule. The
second approach determines the optimal allocation of audit frequency
among all auditable units in the firm. In our review, we discuss both
the deterministic and probabilistic models developed for audit
planning. In addition, game theory models are reviewed to find the
optimal auditing strategy based on the interactions between the
auditors and the clients.
Abstract: Optic disk segmentation plays a key role in the mass
screening of individuals with diabetic retinopathy and glaucoma
ailments. An efficient hardware-based algorithm for optic disk
localization and segmentation would aid for developing an automated
retinal image analysis system for real time applications. Herein,
TMS320C6416DSK DSP board pixel intensity based fractal analysis
algorithm for an automatic localization and segmentation of the optic
disk is reported. The experiment has been performed on color and
fluorescent angiography retinal fundus images. Initially, the images
were pre-processed to reduce the noise and enhance the quality. The
retinal vascular tree of the image was then extracted using canny
edge detection technique. Finally, a pixel intensity based fractal
analysis is performed to segment the optic disk by tracing the origin
of the vascular tree. The proposed method is examined on three
publicly available data sets of the retinal image and also with the data
set obtained from an eye clinic. The average accuracy achieved is
96.2%. To the best of the knowledge, this is the first work reporting
the use of TMS320C6416DSK DSP board and pixel intensity based
fractal analysis algorithm for an automatic localization and
segmentation of the optic disk. This will pave the way for developing
devices for detection of retinal diseases in the future.
Abstract: This paper directs attention to the limitations of the
teacher-centered strategy in teaching. The aim of this study is to draw
more educational attention to learner-centered strategy in order to
shift the emphasis from the traditional concept of teaching to a new
concept in teaching. To begin bridging the traditional concept of
teaching and the new concept, the study will explore the new concept
of teaching to support teaching in Arab World generally and in Iraq
specifically. A qualitative case study orientation was used to collect
data in the form of classroom observations, interviews and field
notes. The teaching practices used by three university instructors are
investigated and according to the findings, some explanations and
recommendations are made.
Abstract: It is necessary to predict a fatigue crack propagation
life for estimation of structural integrity. Because of an uncertainty
and a randomness of a structural behavior, it is also required to
analyze stochastic characteristics of the fatigue crack propagation life
at a specified fatigue crack size. The essential purpose of this study is to find the effect of load ratio
on probability distribution of the fatigue crack propagation life at a
specified grown crack size and to confirm the good probability
distribution in magnesium alloys under various fatigue load ratio
conditions. To investigate a stochastic crack growth behavior, fatigue
crack propagation experiments are performed in laboratory air under
several conditions of fatigue load ratio using AZ31. By Anderson-Darling test, a goodness-of-fit test for probability
distribution of the fatigue crack propagation life is performed. The
effect of load ratio on variability of fatigue crack propagation life is
also investigated.
Abstract: In this paper, we present a four-step ortho-rectification
procedure for real-time geo-referencing of video data from a low-cost
UAV equipped with a multi-sensor system. The basic procedures for
the real-time ortho-rectification are: (1) decompilation of the video
stream into individual frames; (2) establishing the interior camera
orientation parameters; (3) determining the relative orientation
parameters for each video frame with respect to each other; (4)
finding the absolute orientation parameters, using a self-calibration
bundle and adjustment with the aid of a mathematical model. Each
ortho-rectified video frame is then mosaicked together to produce a
mosaic image of the test area, which is then merged with a well
referenced existing digital map for the purpose of geo-referencing
and aerial surveillance. A test field located in Abuja, Nigeria was
used to evaluate our method. Video and telemetry data were collected
for about fifteen minutes, and they were processed using the four-step
ortho-rectification procedure. The results demonstrated that the
geometric measurement of the control field from ortho-images is
more accurate when compared with those from original perspective
images when used to pin point the exact location of targets on the
video imagery acquired by the UAV. The 2-D planimetric accuracy
when compared with the 6 control points measured by a GPS receiver
is between 3 to 5 metres.