Abstract: The goal of this paper is to present the diagnostic
contribution that the screening instrument, Mini-Mental State
Examination-2: Expanded Version (MMSE-2:EV), brings in
detecting the cognitive impairment or in monitoring the progress of
degenerative disorders. The diagnostic signification is underlined by
the interpretation of the MMSE-2:EV scores, resulted from the test
application to patients with mild and major neurocognitive disorders.
The cases were selected from current practice, in order to cover vast
and significant neurocognitive pathology: mild cognitive impairment,
Alzheimer’s disease, vascular dementia, mixed dementia, Parkinson’s
disease, conversion of the mild cognitive impairment into
Alzheimer’s disease. The MMSE-2:EV version was used: it was
applied one month after the initial assessment, three months after the
first reevaluation and then every six months, alternating the blue and
red forms. Correlated with age and educational level, the raw scores
were converted in T scores and then, with the mean and the standard
deviation, the z scores were calculated. The differences of raw scores
between the evaluations were analyzed from the point of view of
statistic signification, in order to establish the progression in time of
the disease. The results indicated that the psycho-diagnostic approach
for the evaluation of the cognitive impairment with MMSE-2:EV is
safe and the application interval is optimal. In clinical settings with a
large flux of patients, the application of the MMSE-2:EV is a safe
and fast psychodiagnostic solution. The clinicians can draw objective
decisions and for the patients: it does not take too much time and
energy, it does not bother them and it doesn’t force them to travel
frequently.
Abstract: A robust sequential nonparametric method is proposed
for adaptation to background noise parameters for real-time. The
distribution of background noise was modelled like to Huber
contamination mixture. The method is designed to operate as an
adaptation-unit, which is included inside a detection subsystem of an
integrated multichannel monitoring system. The proposed method
guarantees the given size of a nonasymptotic confidence set for noise
parameters. Properties of the suggested method are rigorously
proved. The proposed algorithm has been successfully tested in real
conditions of a functioning C-OTDR monitoring system, which was
designed to monitor railways.
Abstract: Multiple User Interference (MUI) considers the
primary problem in Optical Code-Division Multiple Access
(OCDMA), which resulting from the overlapping among the users. In
this article we aim to mitigate this problem by studying an
interference cancellation scheme called successive interference
cancellation (SIC) scheme. This scheme will be tested on two
different detection schemes, spectral amplitude coding (SAC) and
direct detection systems (DS), using partial modified prime (PMP) as
the signature codes. It was found that SIC scheme based on both SAC
and DS methods had a potential to suppress the intensity noise, that is
to say it can mitigate MUI noise. Furthermore, SIC/DS scheme
showed much lower bit error rate (BER) performance relative to
SIC/SAC scheme for different magnitude of effective power. Hence,
many more users can be supported by SIC/DS receiver system.
Abstract: This study compares the intensity of game load among
player positions and between the 1st and the 2nd half of the games.
Two guards, three forwards, and three centers (female basketball
players) participated in this study. The heart rate (HR) and its
development were monitored during two competitive games.
Statistically insignificant differences in the intensity of game load
were recorded between guards, forwards, and centers below and
above 85% of the maximal heart rate (HRmax) and in the mean HR as
% of HRmax (87.81±3.79%, 87.02±4.37%, and 88.76±3.54%,
respectively). Moreover, when the 1st and the 2nd half of the games
were compared in the mean HR (87.89±4.18% vs. 88.14±3.63% of
HRmax), no statistical significance was recorded. This information can
be useful for coaching staff, to manage and to precisely plan the
training process.
Abstract: In recent years, fire accidents have been steadily
increased and the amount of property damage caused by the accidents
has gradually raised. Damaging building structure, fire incidents bring
about not only such property damage but also strength degradation and
member deformation. As a result, the building structure undermines its
structural ability. Examining the degradation and the deformation is
very important because reusing the building is more economical than
reconstruction. Therefore, engineers need to investigate the strength
degradation and member deformation well, and make sure that they
apply right rehabilitation methods. This study aims at evaluating
deformation characteristics of fire damaged and rehabilitated normal
strength concrete beams through both experiments and finite element
analyses. For the experiments, control beams, fire damaged beams and
rehabilitated beams are tested to examine deformation characteristics.
Ten test beam specimens with compressive strength of 21MPa are
fabricated and main test variables are selected as cover thickness of
40mm and 50mm and fire exposure time of 1 hour or 2 hours. After
heating, fire damaged beams are air-recurred for 2 months and
rehabilitated beams are repaired with polymeric cement mortar after
being removed the fire damaged concrete cover. All beam specimens
are tested under four points loading. FE analyses are executed to
investigate the effects of main parameters applied to experimental
study. Test results show that both maximum load and stiffness of the
rehabilitated beams are higher than those of the fire damaged beams.
In addition, predicted structural behaviors from the analyses also show
good rehabilitation effect and the predicted load-deflection curves are
similar to the experimental results. For the further, the proposed
analytical method can be used to predict deformation characteristics of
fire damaged and rehabilitated concrete beams without suffering from
time and cost consuming of experimental process.
Abstract: In this paper, we consider some integrable Heisenberg
Ferromagnet Equations with self-consistent potentials. We study
their Lax representations. In particular we derive their equivalent
counterparts in the form of nonlinear Schr¨odinger type equations.
We present the integrable reductions of the Heisenberg Ferromagnet
Equations with self-consistent potentials. These integrable Heisenberg
Ferromagnet Equations with self-consistent potentials describe
nonlinear waves in ferromagnets with some additional physical fields.
Abstract: Psychopathic disorders are taking an important part in
judge sentencing, especially in Canada. First, we will see how this
phenomenon can be illustrated by the high proportion of psychopath
offenders incarcerated in North American prisons. Many decisions in
Canadians courtrooms seem to point out that psychopathy is often
used as a strong argument by the judges to preserve public safety.
The fact that psychopathy is often associated with violence,
recklessness and recidivism, could explain why many judges consider
psychopathic disorders as an aggravating factor. Generally, the judge
reasoning is based on Article 753 of Canadian Criminal Code related
to dangerous offenders, which is used for individuals who show a
pattern of repetitive and persistent aggressive behaviour. Then we
will show how, with cognitive neurosciences, the psychopath’s
situation in courtrooms would probably change. Cerebral imaging
and news data provided by the neurosciences show that emotional
and volitional functions in psychopath’s brains are impaired.
Understanding these new issues could enable some judges to
recognize psychopathic disorders as a mitigating factor. Finally, two
important questions ought to be raised in this article: can exploring
psychopaths ‘brains really change the judge sentencing in Canadian
courtrooms? If yes, can judges consider psychopathy more as a
mitigating factor than an aggravating factor?
Abstract: The quantitative study of cell mechanics is of
paramount interest, since it regulates the behaviour of the living cells
in response to the myriad of extracellular and intracellular
mechanical stimuli. The novel experimental techniques together with
robust computational approaches have given rise to new theories and
models, which describe cell mechanics as combination of
biomechanical and biochemical processes. This review paper
encapsulates the existing continuum-based computational approaches
that have been developed for interpreting the mechanical responses of
living cells under different loading and boundary conditions. The
salient features and drawbacks of each model are discussed from both
structural and biological points of view. This discussion can
contribute to the development of even more precise and realistic
computational models of cell mechanics based on continuum
approaches or on their combination with microstructural approaches,
which in turn may provide a better understanding of
mechanotransduction in living cells.
Abstract: A bauxite ore can be utilized in Bayer Process, if the
mass ratio of Al2O3 to SiO2 is greater than 10. Otherwise, its FexOy
and SiO2 content should be removed. On the other hand, removal of
TiO2 from the bauxite ore would be beneficial because of both
lowering the red mud residue and obtaining a valuable raw material
containing TiO2 mineral. In this study, the low grade diasporic
bauxite ore of Yalvaç, Isparta, Turkey was roasted under reducing
atmosphere and subjected to magnetic separation. According to the
experimental results, 800°C for reduction temperature and 20000
Gauss of magnetic intensity were found to be the optimum
parameters for removal of iron oxide and rutile from the nonmagnetic
ore. On the other hand, 600°C and 5000 Gauss were
determined to be the optimum parameters for removal of silica from
the non-magnetic ore.
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: 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: 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: Accurate forecasting of fresh produce demand is one
the challenges faced by Small Medium Enterprise (SME)
wholesalers. This paper is an attempt to understand the cause for the
high level of variability such as weather, holidays etc., in demand of
SME wholesalers. Therefore, understanding the significance of
unidentified factors may improve the forecasting accuracy. This
paper presents the current literature on the factors used to predict
demand and the existing forecasting techniques of short shelf life
products. It then investigates a variety of internal and external
possible factors, some of which is not used by other researchers in the
demand prediction process. The results presented in this paper are
further analysed using a number of techniques to minimize noise in
the data. For the analysis past sales data (January 2009 to May 2014)
from a UK based SME wholesaler is used and the results presented
are limited to product ‘Milk’ focused on café’s in derby. The
correlation analysis is done to check the dependencies of variability
factor on the actual demand. Further PCA analysis is done to
understand the significance of factors identified using correlation.
The PCA results suggest that the cloud cover, weather summary and
temperature are the most significant factors that can be used in
forecasting the demand. The correlation of the above three factors
increased relative to monthly and becomes more stable compared to
the weekly and daily demand.
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: 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.
Abstract: In present global scenario, aluminum alloys are
coining the attention of many innovators as competing structural
materials for automotive and space applications. Comparing to other
challenging alloys, especially, 7xxx series aluminum alloys have
been studied seriously because of benefits such as moderate strength;
better deforming characteristics and affordable cost. It is expected
that substitution of aluminum alloys for steels will result in great
improvements in energy economy, durability and recyclability.
However, it is necessary to improve the strength and the formability
levels at low temperatures in aluminum alloys for still better
applications. Aluminum–Zinc–Magnesium with or without other
wetting agent denoted as 7XXX series alloys are medium strength
heat treatable alloys. In addition to Zn, Mg as major alloying
additions, Cu, Mn and Si are the other solute elements which
contribute for the improvement in mechanical properties by suitable
heat treatment process. Subjecting to suitable treatments like age
hardening or cold deformation assisted heat treatments; known as low
temperature thermomechanical treatments (LTMT) the challenging
properties might be incorporated. T6 is the age hardening or
precipitation hardening process with artificial aging cycle whereas T8
comprises of LTMT treatment aged artificially with X% cold
deformation. When the cold deformation is provided after solution
treatment, there is increase in hardness related properties such as
wear resistance, yield and ultimate strength, toughness with the
expense of ductility. During precipitation hardening both hardness
and strength of the samples are increasing. The hardness value may
further improve when room temperature deformation is positively
supported with age hardening known as thermomechanical treatment.
It is intended to perform heat treatment and evaluate hardness, tensile
strength, wear resistance and distribution pattern of reinforcement in
the matrix. 2 to 2.5 and 3 to 3.5 times increase in hardness is reported
in age hardening and LTMT treatments respectively as compared to
as-cast composite. There was better distribution of reinforcements in
the matrix, nearly two fold increase in strength levels and up to 5
times increase in wear resistance are also observed in the present
study.
Abstract: Cyber exercises used to assess the preparedness of a
community against cyber crises, technology failures and Critical
Information Infrastructure (CII) incidents. The cyber exercises also
called cyber crisis exercise or cyber drill, involved partnerships or
collaboration of public and private agencies from several sectors.
This study investigates Organisation Cyber Resilience (OCR) of
participation sectors in cyber exercise called X Maya in Malaysia.
This study used a principal based cyber resilience survey called CSuite
Executive checklist developed by World Economic Forum in
2012. To ensure suitability of the survey to investigate the OCR, the
reliability test was conducted on C-Suite Executive checklist items.
The research further investigates the differences of OCR in ten
Critical National Infrastructure Information (CNII) sectors
participated in the cyber exercise. The One Way ANOVA test result
showed a statistically significant difference of OCR among ten CNII
sectors participated in the cyber exercise.