Abstract: The main objective of this study was to identify
factors and conditions that motivated and encouraged students
towards the math class and the factors that made this class an
attractive and lovely one. To do this end, questionnaires consisting of
15 questions were distributed among 85 math teachers working in
schools of Zahedan. Having collected and reviewed these
questionnaires, it was shown that doing activity in math class
(activity of students while teaching) and previous math teachers'
behaviors have had much impact on encouraging the students
towards mathematics. Separation of educational classroom of
mathematics from the main classroom (which is decorated with crafts
created by students themselves with regard to math book including
article, wall newspaper, figures and formulas), peers, size and
appearance of math book, first grade teachers in each educational
level, among whom the Elementary first grade teachers had more
importance and impact, were among the most influential and
important factors in this regard. Then, school environment, family,
conducting research related to mathematics, its application in daily
life and other courses and studying the history of mathematics were
categorized as important factors that would increase the students’
interest in mathematics.
Abstract: This paper deals with a simulation programs and
technologies using in the educational process for members of the crisis
management. Risk analysis, simulation, preparation and planning are
among the main activities of workers of crisis management. Made
correctly simulation of emergency defines the extent of the danger. On
this basis, it is possible to effectively prepare and plan measures to
minimize damage. The paper is focused on simulation programs that
are trained at the University of Defence. Implementation of the outputs
from simulation programs in decision-making processes of crisis staffs
is one of the main tasks of the research project.
Abstract: This paper deals with a protection of the national and
European infrastructure. It is issue nowadays. The paper deals with
the perspectives and possibilities of "smart solutions" to critical
infrastructure protection. The research project deals with computers
aided technologies are used from the perspective of new, better
protection of selected infrastructure objects. Protection is focused on
communication and information channels. These communication and
information channels are very important for the functioning of the
system of protection of critical infrastructure elements.
Abstract: Chloride resistance in Ultra High Performance
Concrete (UHPC) is determined in this paper. This work deals with
the one dimension chloride transport, which can be potentially
dangerous particularly for the durability of concrete structures. Risk
of reinforcement corrosion due to exposure to the concrete surface to
direct the action of chloride ions (mainly in the form de-icing salts or
groundwater) is dangerously increases. The measured data are
investigated depending on the depth of penetration of chloride ions
into the concrete structure. Comparative measurements with normal
strength concrete are done as well. The experimental results showed
that UHCP have improved resistance of chlorides penetration than
NSC and also chloride diffusion depth is significantly lower in
UHCP.
Abstract: The aim of this work is to present a theoretical analysis of a 2D ultrasound transducer comprised of crossed arrays of metal strips placed on both sides of thin piezoelectric layer (a). Such a structure is capable of electronic beam-steering of generated wavebeam both in elevation and azimuth. In this paper a semi-analytical model of the considered transducer is developed. It is based on generalization of the well-known BIS-expansion method. Specifically, applying the electrostatic approximation, the electric field components on the surface of the layer are expanded into fast converging series of double periodic spatial harmonics with corresponding amplitudes represented by the properly chosen Legendre polynomials. The problem is reduced to numerical solving of certain system of linear equations for unknown expansion coefficients.
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: In this research work, neural networks were applied to
classify two types of hip joint implants based on the relative hip joint
implant side speed and three components of each ground reaction
force. The condition of walking gait at normal velocity was used and
carried out with each of the two hip joint implants assessed. Ground
reaction forces’ kinetic temporal changes were considered in the first
approach followed but discarded in the second one. Ground reaction
force components were obtained from eighteen patients under such
gait condition, half of which had a hip implant type I-II, whilst the
other half had the hip implant, defined as type III by Orthoload®.
After pre-processing raw gait kinetic data and selecting the time
frames needed for the analysis, the ground reaction force components
were used to train a MLP neural network, which learnt to distinguish
the two hip joint implants in the abovementioned condition. Further
to training, unknown hip implant side and ground reaction force
components were presented to the neural networks, which assigned
those features into the right class with a reasonably high accuracy for
the hip implant type I-II and the type III. The results suggest that
neural networks could be successfully applied in the performance
assessment of hip joint implants.
Abstract: The study area is Zaria, located in the basement
complex of northern Nigeria. The rock type forming the major part of
the Zaria batholith is granite. This research work was carried out to
compare the responses of seismic refraction tomography and
resistivity tomography in the same geologic environment and under
the same conditions. Hence, the choice of the site that has a visible
granitic outcrop that extends across a narrow stream channel and is
flanked by unconsolidated overburden, a neutral profile that was
covered by plain overburden and a site with thick lateritic cover
became necessary. The results of the seismic and resistivity
tomography models reveals that seismic velocity and resistivity does
not always simultaneously increase with depth, but their responses in
any geologic environment are determined by changes in the
mechanical and chemical content of the rock types rather than depth.
Abstract: Voltage sags are the most common power quality
disturbance in the distribution system. It occurs due to the fault in the
electrical network or by the starting of a large induction motor and
this can be solved by using the custom power devices such as
Dynamic Voltage Restorer (DVR). In this paper DVR is proposed to
compensate voltage sags on critical loads dynamically. The DVR
consists of VSC, injection transformers, passive filters and energy
storage (lead acid battery). By injecting an appropriate voltage, the
DVR restores a voltage waveform and ensures constant load voltage.
The simulation and experimental results of a DVR using MATLAB
software shows clearly the performance of the DVR in mitigating
voltage sags.
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: 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: 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: 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: During welding, the amount of heat present in weld
zones determines the quality of weldment produced. Thus, the heat
distribution characteristics and its magnitude in weld zones with
respect to process variables such as tool pin-shoulder rotational and
traveling speed during welding is analyzed using thermal finite
element analyses method. For this purpose, transient thermal finite
element analyses are performed to model the temperatures
distribution and its quantities in weld-zones with respect to process
variables such as rotational speed and traveling speed during welding.
Commercially available software Altair HyperWork is used to model
three-dimensional tool pin-shoulder vs. workpieces and to simulate
the friction stir process. The results show that increasing tool
rotational speed, at a constant traveling speed, will increase the
amount of heat generated in weld-zones. In contrary, increasing
traveling speed, at constant tool pin-shoulder rotational speeds, will
reduce the amount of heat generated in weld zones.
Abstract: Frequent, continuous speech training has proven to be
a necessary part of a successful speech therapy process, but
constraints of traveling time and employment dispensation become
key obstacles especially for individuals living in remote areas or for
dependent children who have working parents. In order to ameliorate
speech difficulties with ample guidance from speech therapists, a
website has been developed that supports speech therapy and training
for people with articulation disorders in the standard Thai language.
This web-based program has the ability to record speech training
exercises for each speech trainee. The records will be stored in a
database for the speech therapist to investigate, evaluate, compare
and keep track of all trainees’ progress in detail. Speech trainees can
request live discussions via video conference call when needed.
Communication through this web-based program facilitates and
reduces training time in comparison to walk-in training or
appointments. This type of training also allows people with
articulation disorders to practice speech lessons whenever or
wherever is convenient for them, which can lead to a more regular
training processes.
Abstract: The importance of the formal specification in the
software life cycle is barely concealing to anyone. Formal
specifications use mathematical notation to describe the properties of
information system precisely, without unduly constraining the way in
how these properties are achieved. Having a correct and quality
software specification is not easy task. This study concerns with how
a group of rectifiers can communicate with each other and work to
prepare and produce a correct formal software specification. WBCS
has been implemented based mainly in the proposed supported
cooperative work model and a survey conducted on the existing Webbased
collaborative writing tools. This paper aims to assess the
feasibility of executing the web-based collaboration process using
WBCS. The purpose of conducting this test is to test the system as a
whole for functionality and fitness for use based on the evaluation
test plan.
Abstract: Researches and concerns in power quality gained
significant momentum in the field of power electronics systems over
the last two decades globally. This sudden increase in the number of
concerns over power quality problems is a result of the huge increase
in the use of non-linear loads. In this paper, power quality evaluation
of some distribution networks at Misurata - Libya has been done
using a power quality and energy analyzer (Fluke 437 Series II). The
results of this evaluation are used to minimize the problems of power
quality. The analysis shows the main power quality problems that
exist and the level of awareness of power quality issues with the aim
of generating a start point which can be used as guidelines for
researchers and end users in the field of power systems.
Abstract: This work proposes a fuzzy methodology to support
the investment decisions. While choosing among competitive
investment projects, the methodology makes ranking of projects
using the new aggregation OWA operator – AsPOWA, presented in
the environment of possibility uncertainty. For numerical evaluation
of the weighting vector associated with the AsPOWA operator the
mathematical programming problem is constructed. On the basis of
the AsPOWA operator the projects’ group ranking maximum criteria
is constructed. The methodology also allows making the most
profitable investments into several of the project using the method
developed by the authors for discrete possibilistic bicriteria problems.
The article provides an example of the investment decision-making
that explains the work of the proposed methodology.