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 system is designed to show images which are
related to the query image. Extracting color, texture, and shape
features from an image plays a vital role in content-based image
retrieval (CBIR). Initially RGB image is converted into HSV color
space due to its perceptual uniformity. From the HSV image, Color
features are extracted using block color histogram, texture features
using Haar transform and shape feature using Fuzzy C-means
Algorithm. Then, the characteristics of the global and local color
histogram, texture features through co-occurrence matrix and Haar
wavelet transform and shape are compared and analyzed for CBIR.
Finally, the best method of each feature is fused during similarity
measure to improve image retrieval effectiveness and accuracy.
Abstract: In healthy humans, the cortical brain rhythm shows
specific mu (~6-14 Hz) and beta (~18-24 Hz) band patterns in the
cases of both real and imaginary motor movements. As cerebellar
ataxia is associated with impairment of precise motor movement
control as well as motor imagery, ataxia is an ideal model system in
which to study the role of the cerebellocortical circuit in rhythm
control. We hypothesize that the EEG characteristics of ataxic patients
differ from those of controls during the performance of a
Brain-Computer Interface (BCI) task. Ataxia and control subjects
showed a similar distribution of mu power during cued relaxation.
During cued motor imagery, however, the ataxia group showed
significant spatial distribution of the response, while the control group
showed the expected decrease in mu-band power (localized to the
motor cortex).
Abstract: The European Union Survey on Income and Living
Conditions (EU-SILC) is a popular survey which provides
information on income, poverty, social exclusion and living
conditions of households and individuals in the European Union.
The EU-SILC contains variables which may contain outliers. The
presence of outliers can have an impact on the measures and
indicators used by the EU-SILC. In this paper, we used data sets
from various countries to analyze the presence of outliers. In addition,
we obtain some indicators after removing these outliers, and a
comparison between both situations can be observed. Finally, some
conclusions are obtained.
Abstract: The mineral bioflotation represents a viable
alternative for the evaluation of new processes benefit alternative.
The adsorption bacteria on minerals surfaces will depend mainly on
the type of the microorganism as well as of the studied mineral
surface. In the current study, adhesion of S. carnosus on coal was
studied. Several methods were used as: DRX, Fourier Transform
Infra-Red (FTIR) adhesion isotherms and kinetic. The main goal is to
recovery of organic matter by the microflotation process on coal
particles with biological reagent (S. carnosus). Adhesion tests
revealed that adhesion took place after of 8 h at pH 9. The results
suggest that the adhesion of bacteria to solid substrates can be
considered an abiotic physicochemical process that is consequently
governed by bacterial surface properties such as their specific surface
area, hydrophobicity and surface functionalities. The greatest coal
fine flotability was of 75%, after 5 min of flotation.
Abstract: This research paper aims to identify, analyze and rank
factors affecting labor productivity in Spain with respect to their
relative importance. Using a selected set of 35 factors, a structured
questionnaire survey was utilized as the method to collect data from
companies. Target population is comprised by a random
representative sample of practitioners related with the Spanish
construction industry. Findings reveal the top five ranked factors are
as follows: (1) shortage or late supply of materials; (2) clarity of the
drawings and project documents; (3) clear and daily task assignment;
(4) tools or equipment shortages; (5) level of skill and experience of
laborers. Additionally, this research also pretends to provide simple
and comprehensive recommendations so that they could be
implemented by construction managers for an effective management
of construction labor forces.
Abstract: The paper a summary of the results of concretes with
partial substitution of natural aggregates with recycled concrete is
solved. Design formulas of the concretes were characterised with 20,
40 and 60% substitution of natural 8-16mm fraction aggregates with
a selected recycled concrete of analogous coarse fractions. With the
product samples an evaluation of coarse fraction aggregates influence
on fresh concrete consistency and concrete strength in time was
carried out. The results of concretes with aggregates substitution will
be compared to reference formula containing only the fractions of
natural aggregates.
Abstract: Anultra-low power capacitor less low-dropout voltage
regulator with improved transient response using gain enhanced feed
forward path compensation is presented in this paper. It is based on a
cascade of a voltage amplifier and a transconductor stage in the feed
forward path with regular error amplifier to form a composite gainenhanced
feed forward stage. It broadens the gain bandwidth and thus
improves the transient response without substantial increase in power
consumption. The proposed LDO, designed for a maximum output
current of 100 mA in UMC 180 nm, requires a quiescent current of
69 )A. An undershot of 153.79mV for a load current changes from
0mA to 100mA and an overshoot of 196.24mV for current change of
100mA to 0mA. The settling time is approximately 1.1 )s for the
output voltage undershooting case. The load regulation is of 2.77
)V/mA at load current of 100mA. Reference voltage is generated by
using an accurate band gap reference circuit of 0.8V.The costly
features of SOC such as total chip area and power consumption is
drastically reduced by the use of only a total compensation
capacitance of 6pF while consuming power consumption of 0.096
mW.
Abstract: Currently, biological control programs in greenhouse
crops involve the use, at the same time, several natural enemies
during the crop cycle. Also, large number of plant species grown in
greenhouses, among them, the used cultivars are also wide. However,
the cultivar effects on entomophagous species efficacy (predators and
parasitoids) have been scarcely studied. A new method had been
developed, using the factitious prey or host Ephestia kuehniella. It
allow us to evaluate, under greenhouse or controlled conditions
(semi-field), the cultivar effects on the entomophagous species
effectiveness. The work was carried out in greenhouse tomato crop. It
has been found the biological and ecological activities of predatory
species (Nesidiocoris tenuis) and egg-parasitoid (Trichogramma
achaeae) can be well represented with the use of the factitious prey
or host; being better in the former than the latter. The data found in
the trial are shown and discussed. The developed method could be
applied to evaluate new plant materials before making available to
farmers as commercial varieties, at low costs and easy use.
Abstract: Composite materials have important assets compared
to traditional materials. They bring many functional advantages:
lightness, mechanical resistance and chemical, etc. In the present
study we examine the effect of a circular central notch and a precrack
on the tensile fracture of two woven composite materials. The tensile
tests were applied to a standardized specimen, notched and a
precarcked (orientation of the crack 0°, 45° and 90°). These tensile
tests were elaborated according to an experimental planning design of
the type 23.31 requiring 24 experiments with three repetitions. By the
analysis of regression, we obtained a mathematical model describing
the maximum load according to the influential parameters (hole
diameter, precrack length, angle of a precrack orientation). The
specimens precracked at 90° have a better behavior than those having
a precrack at 45° and still better than those having of the precracks
oriented at 0°. In addition the maximum load is inversely
proportional to the notch size.
Abstract: The paper presents the results of clusterization by
Kohonen self-organizing maps (SOM) applied for analysis of array of
Raman spectra of multi-component solutions of inorganic salts, for
determination of types of salts present in the solution. It is
demonstrated that use of SOM is a promising method for solution of
clusterization and classification problems in spectroscopy of multicomponent
objects, as attributing a pattern to some cluster may be
used for recognition of component composition of the object.
Abstract: The paper describes the experiments and the kinetic
parameters calculus of the gasoil hydrofining. They are presented
experimental results of gasoil hidrofining using Mo and promoted
with Ni on aluminum support catalyst. The authors have adapted a
kinetic model gasoil hydrofining. Using this proposed kinetic model
and the experimental data they have calculated the parameters of the
model. The numerical calculus is based on minimizing the difference
between the experimental sulf concentration and kinetic model
estimation.
Abstract: The article is devoted to the problem of political
discourse and its reflection on mass cognition. This article is
dedicated to describe the myth as one of the main features of political
discourse. The dominance of an expressional and emotional
component in the myth is shown. Precedent phenomenon plays an
important role in distinguishing the myth from the linguistic point of
view. Precedent phenomena show the linguistic cognition, which is
characterized by their fame and recognition. Four types of myths
such as master myths, a foundation myth, sustaining myth,
eschatological myths are observed. The myths about the national idea
are characterized by national specificity. The main aim of the
political discourse with the help of myths is to influence on the mass
consciousness in order to motivate the addressee to certain actions so
that the target purpose is reached owing to unity of forces.
Abstract: This research proposes a novel reconstruction protocol
for restoring missing surfaces and low-quality edges and shapes in
photos of artifacts at historical sites. The protocol starts with the
extraction of a cloud of points. This extraction process is based on
four subordinate algorithms, which differ in the robustness and
amount of resultant. Moreover, they use different -but
complementary- accuracy to some related features and to the way
they build a quality mesh. The performance of our proposed protocol
is compared with other state-of-the-art algorithms and toolkits. The
statistical analysis shows that our algorithm significantly outperforms
its rivals in the resultant quality of its object files used to reconstruct
the desired model.
Abstract: In this study, a comparative analysis of the approaches
associated with the use of neural network algorithms for effective
solution of a complex inverse problem – the problem of identifying
and determining the individual concentrations of inorganic salts in
multicomponent aqueous solutions by the spectra of Raman
scattering of light – is performed. It is shown that application of
artificial neural networks provides the average accuracy of
determination of concentration of each salt no worse than 0.025 M.
The results of comparative analysis of input data compression
methods are presented. It is demonstrated that use of uniform
aggregation of input features allows decreasing the error of
determination of individual concentrations of components by 16-18%
on the average.
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: In this paper we make a temperature investigations in
two type of superposed crimped connections using experimental
determinations. All the samples use 8 copper wire 7.1 x 3 mm2
crimped by two methods: the first method uses one crimp indents and
the second is a proposed method with two crimp indents. The ferrule
is a parallel one. We study the influence of number and position of
crimp indents. The samples are heated in A.C. current at different
current values until steady state heating regime. After obtaining of
temperature values, we compare them and present the conclusion.
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: Frequent pattern mining is the process of finding a
pattern (a set of items, subsequences, substructures, etc.) that occurs
frequently in a data set. It was proposed in the context of frequent
itemsets and association rule mining. Frequent pattern mining is used
to find inherent regularities in data. What products were often
purchased together? Its applications include basket data analysis,
cross-marketing, catalog design, sale campaign analysis, Web log
(click stream) analysis, and DNA sequence analysis. However, one of
the bottlenecks of frequent itemset mining is that as the data increase
the amount of time and resources required to mining the data
increases at an exponential rate. In this investigation a new algorithm
is proposed which can be uses as a pre-processor for frequent itemset
mining. FASTER (FeAture SelecTion using Entropy and Rough sets)
is a hybrid pre-processor algorithm which utilizes entropy and roughsets
to carry out record reduction and feature (attribute) selection
respectively. FASTER for frequent itemset mining can produce a
speed up of 3.1 times when compared to original algorithm while
maintaining an accuracy of 71%.
Abstract: This paper presents a 3D guidance scheme for
Unmanned Aerial Vehicles (UAVs). The proposed guidance scheme
is based on the sliding mode approach using nonlinear sliding
manifolds. Generalized 3D kinematic equations are considered
here during the design process to cater for the coupling between
longitudinal and lateral motions. Sliding mode based guidance
scheme is then derived for the multiple-input multiple-output
(MIMO) system using the proposed nonlinear manifolds. Instead of
traditional sliding surfaces, nonlinear sliding surfaces are proposed
here for performance and stability in all flight conditions. In the
reaching phase control inputs, the bang-bang terms with signum
functions are accompanied with proportional terms in order to reduce
the chattering amplitudes. The Proposed 3D guidance scheme is
implemented on a 6-degrees-of-freedom (6-dof) simulation of a UAV
and simulation results are presented here for different 3D trajectories
with and without disturbances.