Abstract: Kinematic data wisely correlate vector quantities in
space to scalar parameters in time to assess the degree of symmetry
between the intact limb and the amputated limb with respect to a
normal model derived from the gait of control group participants.
Furthermore, these particular data allow a doctor to preliminarily
evaluate the usefulness of a certain rehabilitation therapy.
Kinetic curves allow the analysis of ground reaction forces (GRFs)
to assess the appropriateness of human motion.
Electromyography (EMG) allows the analysis of the fundamental
lower limb force contributions to quantify the level of gait
asymmetry. However, the use of this technological tool is expensive
and requires patient’s hospitalization. This research work suggests
overcoming the above limitations by applying artificial neural
networks.
Abstract: Over the past era, there have been a lot of efforts and
studies are carried out in growing proficient tools for performing
various tasks in big data. Recently big data have gotten a lot of
publicity for their good reasons. Due to the large and complex
collection of datasets it is difficult to process on traditional data
processing applications. This concern turns to be further mandatory
for producing various tools in big data. Moreover, the main aim of
big data analytics is to utilize the advanced analytic techniques
besides very huge, different datasets which contain diverse sizes from
terabytes to zettabytes and diverse types such as structured or
unstructured and batch or streaming. Big data is useful for data sets
where their size or type is away from the capability of traditional
relational databases for capturing, managing and processing the data
with low-latency. Thus the out coming challenges tend to the
occurrence of powerful big data tools. In this survey, a various
collection of big data tools are illustrated and also compared with the
salient features.
Abstract: In this study, first thermoplastic composite materials
/plates that have high ballistic impact resistance were produced. For
this purpose, the thermoplastic prepreg and the vacuum bagging
technique were used to produce a composite material. Thermoplastic
prepregs (resin-impregnated fiber) that are supplied ready to be used,
namely high-density polyethylene (HDPE) was chosen as matrix and
unidirectional glass fiber was used as reinforcement. In order to
compare the fiber configuration effect on mechanical properties,
unidirectional and biaxial prepregs were used. Then the
microstructural properties of the composites were investigated with
scanning electron microscopy (SEM) analysis. Impact properties of
the composites were examined by Charpy impact test and tensile
mechanical tests and then the effects of ultraviolet irradiation were
investigated on mechanical performance.
Abstract: With demand for primary energy continuously
growing, search for renewable and efficient energy sources has been
high on agenda of our society. One of the most promising energy
sources is biogas technology. Residues coming from dairy industry
and milk processing could be used in biogas production; however,
low efficiency and high cost impede wide application of such
technology. One of the main problems is management and conversion
of organic residues through the anaerobic digestion process which is
characterized by acidic environment due to the low whey pH (
Abstract: The measured data obtained from sensors in
continuous monitoring of civil structures are mainly used for modal
identification and damage detection. Therefore, when modal
identification analysis is carried out the quality in the identification of
the modes will highly influence the damage detection results. It is
also widely recognized that the usefulness of the measured data used
for modal identification and damage detection is significantly
influenced by the number and locations of sensors. The objective of
this study is the numerical implementation of two widely known
optimum sensor placement methods in beam-like structures.
Abstract: The global demand for continuous and eco-friendly
renewable energy as alternative to fossils fuels is large and ever
growing in nowadays. This paper will focus on capability of Vortex
Induced Vibration (VIV) phenomenon in generating alternative
energy for offshore platform application. In order to maximize the
potential of energy generation, the effects of lock in phenomenon and
different geometries of cylinder were studied in this project. VIV is
the motion induced on bluff body which creates alternating lift forces
perpendicular to fluid flow. Normally, VIV is unwanted in order to
prevent mechanical failure of the vibrating structures. But in this
project, instead of eliminating these vibrations, VIV will be exploited
to transform these vibrations into a valuable resource of energy.
Abstract: Malathion (ML) is a well known pesticide commonly
used in many agricultural and non-agricultural processes. Its toxicity
has been attributed primarily to the accumulation of acetylcholine
(Ach) at nerve junctions, due to the inhibition of acetylcholinesterase
(AChE). The aim of the current research was to study the protective
effect of the melissa plant extract against reproductive impairment
induced by malathion in 32 male albino rats, and the biological
experiment was divided into four groups (8 in each) that given
malathion (27 mg/kg; 1/50 of the LD50 for an oral dose) and/or
Melissa officinalis (MO) extract (200mg/kg/day) by gavages
technique. The sperm counts, sperm motility, sperm morphology,
FSH, LH, and testosterone levels had been determined in testes
homogenate at the end of the experiment. It is worthy to report that,
rats treated with melissa extract did not show a significant difference
when compared with the control group, while rats given malathion
alone had significantly lower sperm count, sperm motility, and
significantly higher abnormal sperm numbers, than the untreated
control rats as well as having significantly lower serum FSH, LH, and
testosterone levels compared with the control group. Administrations
of melissa extract restore all mentioned histological parameters
towards the control group and the melissa extract had a strong
positive protective effect against malathion toxicity. Results the of
biological parameters were confirmed by the histological
examination of rat testes and indicated that, both control and melissa
groups showing normal seminiferous tubules, while malathion group
testicular tissues had necrosis, edema in the seminiferous tubules and
degeneration of spermatogonial cells lining the seminiferous tubules
with incomplete spermatogenesis. The use of melissa against
malathion improved the histological picture and showing normal
seminiferous tubules with complete spermatogenesis and almost there
was no histopathological changes could be noted.
Abstract: Opportunistic routing is used, where the network has
the features like dynamic topology changes and intermittent network
connectivity. In Delay tolerant network or Disruption tolerant
network opportunistic forwarding technique is widely used. The key
idea of opportunistic routing is selecting forwarding nodes to forward
data packets and coordination among these nodes to avoid duplicate
transmissions. This paper gives the analysis of pros and cons of
various opportunistic routing techniques used in MANET.
Abstract: This paper deals with the problem of passivity
analysis for stochastic neural networks with leakage, discrete and
distributed delays. By using delay partitioning technique, free
weighting matrix method and stochastic analysis technique, several
sufficient conditions for the passivity of the addressed neural
networks are established in terms of linear matrix inequalities
(LMIs), in which both the time-delay and its time derivative can be
fully considered. A numerical example is given to show the
usefulness and effectiveness of the obtained results.
Abstract: Pomegranate (Punica granatum L.) is an ancient fruit of great medical interest and rich source of antioxidants. Pesticides as dimethoate play a crucial role in the occurrence many diseases in plants, animal and human. Therefore the ability of Pomegranate (Punica granatum L.) to alleviate hepatotoxicity induced by organophosphate pesticide dimethoate was investigated. Albino male rats were divided randomly into 4 groups and kept at 7 animals per group in an environmentally controlled condition for 6 weeks. The first group was served as a control group (basal diet), the second group fed on basal diet supplemented with 5% freeze dried pomegranate seeds, the third group fed on 20 ppm dimethoate contaminated diet and the last group fed on dimethoate contaminated diet supplemented with 5% freeze dried pomegranate seeds. The results revealed that administration of dimethoate caused high significant increased in liver functions: alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP) activities as well as lipid peroxide (malonaldhyde, MDA); on the other hand high significant decreased on glutathione (GSH), glutathione peroxidase (GPx), albumin and total protein were observed. However addition of 5% freeze dried pomegranate seeds significantly improved all previously mentioned parameters. These results indicate the dimethoate induced hepatotoxicity and highlight the protective effect of pomegranate seeds as a potential protective agent against dimethoate induced hepatotoxicity. This may be attributed to the powerful antioxidants (polyphenols, total phenols, and total flavonoids) which present in high levels in pomegranate as well as improving the immunity by activation of antioxidant enzymes GSH and GPx.
Abstract: This paper aims at finding a suitable neural network
for monitoring congestion level in electrical power systems. In this
paper, the input data has been framed properly to meet the target
objective through supervised learning mechanism by defining normal
and abnormal operating conditions for the system under study. The
congestion level, expressed as line congestion index (LCI), is
evaluated for each operating condition and is presented to the NN
along with the bus voltages to represent the input and target data.
Once, the training goes successful, the NN learns how to deal with a
set of newly presented data through validation and testing
mechanism. The crux of the results presented in this paper rests on
performance comparison of a multi-layered feed forward neural
network with eleven types of back propagation techniques so as to
evolve the best training criteria. The proposed methodology has been
tested on the standard IEEE-14 bus test system with the support of
MATLAB based NN toolbox. The results presented in this paper
signify that the Levenberg-Marquardt backpropagation algorithm
gives best training performance of all the eleven cases considered in
this paper, thus validating the proposed methodology.
Abstract: The article presents the results of the application of
artificial neural networks to separate the fluorescent contribution of
nanodiamonds used as biomarkers, adsorbents and carriers of drugs
in biomedicine, from a fluorescent background of own biological
fluorophores. The principal possibility of solving this problem is
shown. Use of neural network architecture let to detect fluorescence
of nanodiamonds against the background autofluorescence of egg
white with high accuracy - better than 3 ug/ml.
Abstract: Color Histogram is considered as the oldest method
used by CBIR systems for indexing images. In turn, the global
histograms do not include the spatial information; this is why the
other techniques coming later have attempted to encounter this
limitation by involving the segmentation task as a preprocessing step.
The weak segmentation is employed by the local histograms while
other methods as CCV (Color Coherent Vector) are based on strong
segmentation. The indexation based on local histograms consists of
splitting the image into N overlapping blocks or sub-regions, and
then the histogram of each block is computed. The dissimilarity
between two images is reduced, as consequence, to compute the
distance between the N local histograms of the both images resulting
then in N*N values; generally, the lowest value is taken into account
to rank images, that means that the lowest value is that which helps to
designate which sub-region utilized to index images of the collection
being asked. In this paper, we make under light the local histogram
indexation method in the hope to compare the results obtained against
those given by the global histogram. We address also another
noteworthy issue when Relying on local histograms namely which
value, among N*N values, to trust on when comparing images, in
other words, which sub-region among the N*N sub-regions on which
we base to index images. Based on the results achieved here, it seems
that relying on the local histograms, which needs to pose an extra
overhead on the system by involving another preprocessing step
naming segmentation, does not necessary mean that it produces better
results. In addition to that, we have proposed here some ideas to
select the local histogram on which we rely on to encode the image
rather than relying on the local histogram having lowest distance with
the query histograms.
Abstract: In this paper, strontium ferrite (SrO.6Fe2O3) was
synthesized by the sol-gel auto-combustion process. The thermal
behavior of powder obtained from self-propagating combustion of
initial gel was evaluated by simultaneous differential thermal analysis
(DTA) and thermo gravimetric (TG), from room temperature to
1200°C. The as-burnt powder was calcined at various temperatures
from 700-900°C to achieve the single-phase Sr-ferrite. Phase
composition, morphology and magnetic properties were investigated
using X-ray diffraction (XRD), transmission electron microscopy
(TEM) and vibrating sample magnetometry (VSM) techniques.
Results showed that the single-phase and nano-sized hexagonal
strontium ferrite particles were formed at calcination temperature of
800°C with crystallite size of 27 nm and coercivity of 6238 Oe.
Abstract: One of the most important tasks in urban remote
sensing is the detection of impervious surfaces (IS), such as roofs and
roads. However, detection of IS in heterogeneous areas still remains
one of the most challenging tasks. In this study, detection of concrete
roof using an object-based approach was proposed. A new rule-based
classification was developed to detect concrete roof tile. This
proposed rule-based classification was applied to WorldView-2
image and results showed that the proposed rule has good potential to
predict concrete roof material from WorldView-2 images, with 85%
accuracy.
Abstract: The article presents the trends in Georgian wine
market development and evaluates the competitive advantages of
Georgia to enter the wine market based on its customs, traditions and
historical practices combined with modern technologies.
In order to analyze the supply of wine, dynamics of vineyard land
area and grape varieties are discussed, trends in wine production are
presented, trends in export and import are evaluated, local wine
market, its micro and macro environments are studied and analyzed
based on the interviews with experts and analysis of initial recording
materials.
For strengthening its position on the international market, the level
of competitiveness of Georgian wine is defined, which is evaluated
by “ex-ante” and “ex-post” methods, as well as by four basic and two
additional factors of the Porter’s diamond method; potential
advantages and disadvantages of Georgian wine are revealed.
Conclusions are made by identifying the factors that hinder the
development of Georgian wine market. Based on the conclusions,
relevant recommendations are developed.
Abstract: The paper discusses economic policy of Georgia
aiming to increase national competitiveness as well as the tools and
means which will help to improve the competitiveness of the country.
The sectors of the economy, in which the country can achieve the
competitive advantage, are studied. It is noted that the country’s
economic policy plays an important role in obtaining and maintaining
the competitive advantage - authority should take measures to ensure
high level of education; scientific and research activities should be
funded by the state; foreign direct investments should be attracted
mainly in science-intensive industries; adaptation with the latest
scientific achievements of the modern world and deepening of
scientific and technical cooperation. Stable business environment and
export oriented strategy is the basis for the country’s economic
growth.
As the outcome of the research, the paper suggests the strategy for
improving competitiveness in Georgia; recommendations are
provided based on relevant conclusions.
Abstract: Recent perceived climate variability raises concerns
with unprecedented hydrological phenomena and extremes.
Distribution and circulation of the waters of the Earth become
increasingly difficult to determine because of additional uncertainty
related to anthropogenic emissions. The world wide observed
changes in the large-scale hydrological cycle have been related to an
increase in the observed temperature over several decades. Although
the effect of change in climate on hydrology provides a general
picture of possible hydrological global change, new tools and
frameworks for modelling hydrological series with nonstationary
characteristics at finer scales, are required for assessing climate
change impacts. Of the downscaling techniques, dynamic
downscaling is usually based on the use of Regional Climate Models
(RCMs), which generate finer resolution output based on atmospheric
physics over a region using General Circulation Model (GCM) fields
as boundary conditions. However, RCMs are not expected to capture
the observed spatial precipitation extremes at a fine cell scale or at a
basin scale. Statistical downscaling derives a statistical or empirical
relationship between the variables simulated by the GCMs, called
predictors, and station-scale hydrologic variables, called predictands.
The main focus of the paper is on the need for using statistical
downscaling techniques for projection of local hydrometeorological
variables under climate change scenarios. The projections can be then
served as a means of input source to various hydrologic models to
obtain streamflow, evapotranspiration, soil moisture and other
hydrological variables of interest.
Abstract: As an entity of the tourism system, local communities
were considered have better understanding of their region as well as
influenced positively or negatively by the tourism activities in the
region. This paper aimed to study role of community involvement in
the development of ecotourism at Kintamani Bali from two
perspectives of view, i.e. participation in the process of initiatives and
participation in the utilizing the economic benefits of tourism.
Thorough participation as an antecedent of social capital form, the
sustainability of ecotourism at Kintamani could be expected.
Abstract: A method is proposed for stable detection of
seismoacoustic sources in C-OTDR systems that guarantee given
upper bounds for probabilities of type I and type II errors. Properties
of the proposed method are rigorously proved. The results of
practical applications of the proposed method in a real C-OTDRsystem
are presented.