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: 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: Audio-lingual Method (ALM) is a teaching approach
that is claimed that ineffective for teaching second/foreign languages.
Because some linguists and second/foreign language teachers believe
that ALM is a rote learning style. However, this study is done on a
belief that ALM will be able to solve Thais’ English speaking
problem. This paper aims to report the findings on teaching English
speaking to adult learners with an “adapted ALM”, one distinction of
which is to use Thai as the medium language of instruction.
The participants are consisted of 9 adult learners. They were
allowed to speak English more freely using both the materials
presented in the class and their background knowledge of English. At
the end of the course, they spoke English more fluently, more
confidently, to the extent that they applied what they learnt both in
and outside the class.
Abstract: The lactic acid bacteria (LAB) were isolated from
10 samples of fermented foods (Sa-tor-dong and Bodo) in South
locality of Thailand. The 23 isolates of lactic acid bacteria were
selected, which were exhibited a clear zone and growth on MRS
agar supplemented with CaCO3. All of lactic acid bacteria were
tested on morphological and biochemical. The result showed that
all isolates were Gram’s positive, non-spore forming but only
10 isolates displayed catalase negative. The 10 isolates including
BD1 .1, BD 1.2, BD 2.1, BD2.2, BD 2.3, BD 3.1, BD 4.1, BD 5.2,
ST 4.1 and ST 5.2 were selected for inhibition activity
determination. Only 2 strains (ST 4.1 and BD 2.3) showed
inhibition zone on agar, when using Escherichia coli sp. as target
strain. The ST 4.1 showed highest inhibition zone on agar, which
was selected for probiotic property testing. The ST4.1 isolate
could grow in MRS broth containing a high concentration of
sodium chloride 6%, bile salts 7%, pH 4-10 and vary temperature
at 15-45°C.
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: Estimation of a proportion has many applications in
economics and social studies. A common application is the estimation
of the low income proportion, which gives the proportion of people
classified as poor into a population. In this paper, we present this
poverty indicator and propose to use the logistic regression estimator
for the problem of estimating the low income proportion. Various
sampling designs are presented. Assuming a real data set obtained
from the European Survey on Income and Living Conditions, Monte
Carlo simulation studies are carried out to analyze the empirical
performance of the logistic regression estimator under the various
sampling designs considered in this paper. Results derived from
Monte Carlo simulation studies indicate that the logistic regression
estimator can be more accurate than the customary estimator under
the various sampling designs considered in this paper. The stratified
sampling design can also provide more accurate results.
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: In order to investigate the effect of Plant Growth
Promoting Rhizobacteria (PGPR) and rhizobium bacteria on grain
yield and some agronomic traits of mungbean (Vigna radiate L.), an
experiment was carried out based on randomized complete block
design with three replications in Malekshahi, Ilam province, Iran
during 2012-2013 cropping season. Experimental treatments
consisted of control treatment, inoculation with rhizobium bacteria,
rhizobium bacteria and Azotobacter, rhizobium bacteria and
Azospirillum, rhizobium bacteria and Pseudomonas, rhizobium
bacteria, Azotobacter and Azospirillum, rhizobium bacteria,
Azotobacter and Pseudomonas, rhizobium bacteria, Azospirillum and
Pseudomonas and rhizobium bacteria, Azotobacter, Azospirillum and
Pseudomonas. The results showed that the effect of PGPR and
rhizobium bacteria were significant affect on grain and its
components in mungbean plant. Grain yield significantly increased
by PGPR and rhizobium bacteria, so that the maximum grain yield
was obtained from rhizobium bacteria + Azospirillum +
Pseudomonas with the amount of 2287 kg.ha-1 as compared to
control treatment. Excessive application of chemical fertilizers causes
environmental and economic problems. That is, the overfertilization
of P and N leads to pollution due to soil erosion and runoff water, so
the use of PGPR and rhizobium bacteria can be justified due to
reduce input costs, increase in grain yield and environmental friendly.
Abstract: In this paper, we propose a multi-agent intelligent
system that is used for monitoring the health conditions of elderly
people. Monitoring the health condition of elderly people is a
complex problem that involves different medical units and requires
continuous monitoring. Such expert system is highly needed in rural
areas because of inadequate number of available specialized
physicians or nurses. Such monitoring must have autonomous
interactions between these medical units in order to be effective. A
multi-agent system is formed by a community of agents that
exchange information and proactively help one another to achieve the
goal of elderly monitoring. The agents in the developed system are
equipped with intelligent decision maker that arms them with the
rule-based reasoning capability that can assist the physicians in
making decisions regarding the medical condition of elderly people.
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: In the 13th Malaysia’s General Elections held in 2013,
it was observed that large numbers of urban constituencies saw
strongly decisive young voters (between 21-39 age group) determine
the outcome in their favour. Also, the Elections Commission had
approximated that 70% of some 4.2 million unregistered voters at the
time were citizens aged between 21 and 40 years old. If they are not
already considered an important form of political leverage, 450,000
young Malaysians turn 21 years old each year. Further compounding
this fact were the 2.4 million new voters registered in 2012, which at
the time constituted almost 30% of the entire voting population. This
article discusses the importance of issues for the youth, with
reference to the university students in Malaysia in their decision
making on polling day.
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: In development of floating photovoltaic generation
system, finding a suitable place of installation is as important as
development of economically feasible and stable structure. Especially
since floating photovoltaic system has its facility floating on water
surface, it is extremely important to review the effects of weather
conditions such as wind, water flow and floating matters, various
factors (such as fogs) that can reduce generation efficiency, possibility
of connection with power system, and legal restrictions. The method of
investigating suitable area and resource for development of
tracking-type floating photovoltaic generation system was proposed in
this paper, which can be used for development of floating and ocean
photovoltaic system in the future.
Abstract: Business interpreting talents are in badly need for local
economic development, but currently there are problems of traditional
business interpreting training mode in China. In view of the good
opportunity for college business interpreters provided by international
trading center development in Qingdao China and with the aim of
being in line with market demand and enhancing business interpreters'
employment competitive advantage, this paper aims to explore how to
cultivate interdisciplinary business interpreting talents based on
market demand.
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.