Abstract: In internet of things (IoT) system, the communication
scheme with reliability and low power is required to connect a
terminal. Cooperative communication can achieve reliability and
lower power than multiple-input multiple-output (MIMO) system.
Cooperative communication increases the reliability with low
power, but decreases a throughput. It has a weak point that the
communication throughput is decreased. In this paper, a novel scheme
is proposed to increase the communication throughput. The novel
scheme is a transmission structure that increases transmission rate.
A decoding scheme according to the novel transmission structure is
proposed. Simulation results show that the proposed scheme increases
the throughput without bit error rate (BER) performance degradation.
Abstract: At the present time, awareness, education, computer
simulation and information systems protection are very serious and
relevant topics. The article deals with perspectives and possibilities of
implementation of emergence or natural hazard threats into the
system which is developed for communication among members of
crisis management staffs. The Czech Hydro-Meteorological Institute
with its System of Integrated Warning Service resents the largest
usable base of information. National information systems are connected to foreign systems,
especially to flooding emergency systems of neighboring countries,
systems of European Union and international organizations where the
Czech Republic is a member. Use of outputs of particular information
systems and computer simulations on a single communication
interface of information system for communication among members
of crisis management staff and setting the site interoperability in the
net will lead to time savings in decision-making processes in solving
extraordinary events and crisis situations. Faster managing of an
extraordinary event or a crisis situation will bring positive effects and
minimize the impact of negative effects on the environment.
Abstract: The present paper attempts to investigate the
prediction of air entrainment rate and aeration efficiency of a free
overfall jets issuing from a triangular sharp crested weir by using
regression based modelling. The empirical equations, Support vector
machine (polynomial and radial basis function) models and the linear
regression techniques were applied on the triangular sharp crested
weirs relating the air entrainment rate and the aeration efficiency to
the input parameters namely drop height, discharge, and vertex angle.
It was observed that there exists a good agreement between the
measured values and the values obtained using empirical equations,
Support vector machine (Polynomial and rbf) models and the linear
regression techniques. The test results demonstrated that the SVM
based (Poly & rbf) model also provided acceptable prediction of the
measured values with reasonable accuracy along with empirical
equations and linear regression techniques in modelling the air
entrainment rate and the aeration efficiency of a free overfall jets
issuing from triangular sharp crested weir. Further sensitivity analysis
has also been performed to study the impact of input parameter on the
output in terms of air entrainment rate and aeration efficiency.
Abstract: In this paper, to model a real life wind turbine, a
probabilistic approach is proposed to model the dynamics of the
blade elements of a small axial wind turbine under extreme stochastic
wind speeds conditions. It was found that the power and the torque
probability density functions even-dough decreases at these extreme
wind speeds but are not infinite. Moreover, we also fund that it
is possible to stabilize the power coefficient (stabilizing the output
power)above rated wind speeds by turning some control parameters.
This method helps to explain the effect of turbulence on the quality
and quantity of the harness power and aerodynamic torque.
Abstract: Laban Movement Analysis (LMA), developed in the
dance community over the past seventy years, is an effective method
for observing, describing, notating, and interpreting human
movement to enhance communication and expression in everyday
and professional life. Many applications that use motion capture data
might be significantly leveraged if the Laban qualities will be
recognized automatically. This paper presents an automated
recognition method of Laban qualities from motion capture skeletal
recordings and it is demonstrated on the output of Microsoft’s Kinect
V2 sensor.
Abstract: Multiple-input multiple-output (MIMO) radar has
received increasing attention in recent years. MIMO radar has many
advantages over conventional phased array radar such as target
detection,resolution enhancement, and interference suppression. In
this paper, the results are presented from a simulation study of MIMO
uniformly-spaced linear array (ULA) antennas. The performance is
investigated under varied parameters, including varied array size,
pseudo random (PN) sequence length, number of snapshots, and
signal to noise ratio (SNR). The results of MIMO are compared to a
traditional array antenna.
Abstract: In order to achieve high data rate and increase the
spectral efficiency, multiple input multiple output (MIMO) system has
been proposed. However, multiple antennas are limited by size and
cost. Therefore, recently developed cooperative diversity scheme,
which profits the transmit diversity only with the existing hardware by
constituting a virtual antenna array, can be a solution. However, most
of the introduced cooperative techniques have a common fault of
decreased transmission rate because the destination should receive the
decodable compositions of symbols from the source and the relay. In
this paper, we propose a cooperative cyclic delay diversity (CDD)
scheme that use hierarchical modulation. This scheme is free from the
rate loss and allows seamless cooperative communication.
Abstract: This study integrates a larger research empirical
project that examines second language (SL) learners’ profiles and
valid procedures to perform complete and diagnostic assessment in
schools. 102 learners of Portuguese as a SL aged 7 and 17 years
speakers of distinct home languages were assessed in several
linguistic tasks. In this article, we focused on writing performance in
the specific task of narrative essay composition. The written outputs
were measured using the score in six components adapted from an
English SL assessment context (Alberta Education): linguistic
vocabulary, grammar, syntax, strategy, socio-linguistic, and
discourse. The writing processes and strategies in Portuguese
language used by different immigrant students were analysed to
determine features and diversity of deficits on authentic texts
performed by SL writers. Differentiated performance was based on
the diversity of the following variables: grades, previous schooling,
home language, instruction in first language, and exposure to
Portuguese as Second Language. Indo-Aryan languages speakers
showed low writing scores compared to their peers and the type of
language and respective cognitive mapping (such as Mandarin and
Arabic) was the predictor, not linguistic distance. Home language
instruction should also be prominently considered in further research
to understand specificities of cognitive academic profile in a
Romance languages learning context. Additionally, this study also
examined the teachers’ representations that will be here addressed to
understand educational implications of second language teaching in
psychological distress of different minorities in schools of specific
host countries.
Abstract: An approach was evaluated for the retrieval of soil
moisture of bare soil surface using bistatic scatterometer data in the
angular range of 200 to 700 at VV- and HH- polarization. The
microwave data was acquired by specially designed X-band (10
GHz) bistatic scatterometer. The linear regression analysis was done
between scattering coefficients and soil moisture content to select the
suitable incidence angle for retrieval of soil moisture content. The 250
incidence angle was found more suitable. The support vector
regression analysis was used to approximate the function described
by the input output relationship between the scattering coefficient and
corresponding measured values of the soil moisture content. The
performance of support vector regression algorithm was evaluated by
comparing the observed and the estimated soil moisture content by
statistical performance indices %Bias, root mean squared error
(RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias,
root mean squared error (RMSE) and Nash-Sutcliffe Efficiency
(NSE) were found 2.9451, 1.0986 and 0.9214 respectively at HHpolarization.
At VV- polarization, the values of %Bias, root mean
squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were
found 3.6186, 0.9373 and 0.9428 respectively.
Abstract: Tool, Die and Mould-making (TDM) firms have been
known to play a pivotal role in the growth and development of the
manufacturing sectors in most economies. Their output contributes
significantly to the quality, cost and delivery speed of final
manufactured parts. Unfortunately, the South African Tool, Die and
Mould-making manufacturers have not been competing on the local
or global market in a significant way. This reality has hampered the
productivity and growth of the sector thus attracting intervention. The
paper explores the shortcomings South African toolmakers have to
overcome to restore their competitive position globally. Results from
a global benchmarking survey on the tooling sector are used to
establish a roadmap of what South African toolmakers can do to
become a productive, World Class force on the global market.
Abstract: Particle size distribution, the most important
characteristics of aerosols, is obtained through electrical
characterization techniques. The dynamics of charged nanoparticles
under the influence of electric field in Electrical Mobility
Spectrometer (EMS) reveals the size distribution of these particles.
The accuracy of this measurement is influenced by flow conditions,
geometry, electric field and particle charging process, therefore by
the transfer function (transfer matrix) of the instrument. In this work,
a wire-cylinder corona charger was designed and the combined fielddiffusion
charging process of injected poly-disperse aerosol particles
was numerically simulated as a prerequisite for the study of a
multichannel EMS. The result, a cloud of particles with no uniform
charge distribution, was introduced to the EMS. The flow pattern and
electric field in the EMS were simulated using Computational Fluid
Dynamics (CFD) to obtain particle trajectories in the device and
therefore to calculate the reported signal by each electrometer.
According to the output signals (resulted from bombardment of
particles and transferring their charges as currents), we proposed a
modification to the size of detecting rings (which are connected to
electrometers) in order to evaluate particle size distributions more
accurately. Based on the capability of the system to transfer
information contents about size distribution of the injected particles,
we proposed a benchmark for the assessment of optimality of the
design. This method applies the concept of Von Neumann entropy
and borrows the definition of entropy from information theory
(Shannon entropy) to measure optimality. Entropy, according to the
Shannon entropy, is the ''average amount of information contained in
an event, sample or character extracted from a data stream''.
Evaluating the responses (signals) which were obtained via various
configurations of detecting rings, the best configuration which gave
the best predictions about the size distributions of injected particles,
was the modified configuration. It was also the one that had the
maximum amount of entropy. A reasonable consistency was also
observed between the accuracy of the predictions and the entropy
content of each configuration. In this method, entropy is extracted
from the transfer matrix of the instrument for each configuration.
Ultimately, various clouds of particles were introduced to the
simulations and predicted size distributions were compared to the
exact size distributions.
Abstract: Voting algorithms are extensively used to make
decisions in fault tolerant systems where each redundant module
gives inconsistent outputs. Popular voting algorithms include
majority voting, weighted voting, and inexact majority voters. Each
of these techniques suffers from scenarios where agreements do not
exist for the given voter inputs. This has been successfully overcome
in literature using fuzzy theory. Our previous work concentrated on a
neuro-fuzzy algorithm where training using the neuro system
substantially improved the prediction result of the voting system.
Weight training of Neural Network is sub-optimal. This study
proposes to optimize the weights of the Neural Network using
Artificial Bee Colony algorithm. Experimental results show the
proposed system improves the decision making of the voting
algorithms.
Abstract: To tackle the air pollution issues, Plug-in Hybrid
Electric Vehicles (PHEVs) are proposed as an appropriate solution.
Charging a large amount of PHEV batteries, if not controlled, would
have negative impacts on the distribution system. The control process
of charging of these vehicles can be centralized in parking lots that
may provide a chance for better coordination than the individual
charging in houses. In this paper, an optimization-based approach is
proposed to determine the optimum PHEV parking capacities in
candidate nodes of the distribution system. In so doing, a profile for
charging and discharging of PHEVs is developed in order to flatten
the network load profile. Then, this profile is used in solving an
optimization problem to minimize the distribution system losses. The
outputs of the proposed method are the proper place for PHEV
parking lots and optimum capacity for each parking. The application
of the proposed method on the IEEE-34 node test feeder verifies the
effectiveness of the method.
Abstract: The current paper presents an extensive bottom-up
framework for assessing building sector-specific vulnerability to
climate change: energy supply and demand. The research focuses on
the application of downscaled seasonal models for estimating energy
performance of buildings in Greece. The ARW-WRF model has
been set-up and suitably parameterized to produce downscaled
climatological fields for Greece, forced by the output of the CFSv2
model. The outer domain, D01/Europe, included 345 x 345 cells of
horizontal resolution 20 x 20 km2 and the inner domain, D02/Greece,
comprised 180 x 180 cells of 5 x 5 km2 horizontal resolution. The
model run has been setup for a period with a forecast horizon of 6
months, storing outputs on a six hourly basis.
Abstract: The output error of the globoidal cam mechanism can
be considered as a relevant indicator of mechanism performance,
because it determines kinematic and dynamical behavior of
mechanical transmission. Based on the differential geometry and the
rigid body transformations, the mathematical model of surface
geometry of the globoidal cam is established. Then we present the
analytical expression of the output error (including the transmission
error and the displacement error along the output axis) by considering
different manufacture and assembly errors. The effects of the center
distance error, the perpendicular error between input and output axes
and the rotational angle error of the globoidal cam on the output error
are systematically analyzed. A globoidal cam mechanism which is
widely used in automatic tool changer of CNC machines is applied for
illustration. Our results show that the perpendicular error and the
rotational angle error have little effects on the transmission error but
have great effects on the displacement error along the output axis. This
study plays an important role in the design, manufacture and assembly
of the globoidal cam mechanism.
Abstract: In developing countries, one of the most important
restrictions about the economic growth is the lack of national savings
which are supposed to finance the investments. In order to overcome
this restriction and achieve the higher rate of economic growth by
increasing the level of output, countries choose the external
borrowing. However, there is a dispute in the literature over the
correlation between external debt and economic growth. The aim of
this study is to examine the effects of external debt on Turkish
economic growth by using VAR analysis with the quarterly data over
the period of 2002:01-2014:04. In this respect, Johansen
Cointegration Test, Impulse- Response Function and Variance
Decomposition Tests will be used for analyses. Empirical findings
show that there is no cointegration in the long run.
Abstract: Nowadays, technological progress is one of the most
important components of economic growth and the efficiency of
R&D activities is particularly essential for countries. This study is an
attempt to analyze the R&D efficiencies of EU countries. The
indicators related to R&D efficiencies should be determined in
advance in order to use DEA. For this reason a list of input and
output indicators are derived from the literature review. Considering
the data availability, a final list is given for the numerical analysis for
future research.
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: The article describes the effect of the replacement of
the used reference coordinate system in the georeferencing of an old
map of Europe. The map was georeferenced into three types of
projection – the equal-area conic (original cartographic projection),
cylindrical Plate Carrée and cylindrical Mercator map projection. The
map was georeferenced by means of the affine and the second-order
polynomial transformation. The resulting georeferenced raster
datasets from the Plate Carrée and Mercator projection were
projected into the equal-area conic projection by means of projection
equations. The output is the comparison of drawn graphics, the
magnitude of standard deviations for individual projections and types
of transformation.
Abstract: In recent research copper and manganese systems
were found to be the most active in CO and organic compounds
oxidation among the base catalysts. The mixed copper manganese
oxide has been widely studied in oxidation reactions because of their
higher activity at low temperatures in comparison with single oxide
catalysts. The results showed that the formation of spinel
CuxMn3−xO4 in the oxidized catalyst is responsible for the activity
even at room temperature. That is why the most of the investigations
are focused on the hopcalite catalyst (CuMn2O4) as the best coppermanganese
catalyst. Now it’s known that this is true only for CO
oxidation, but not for mixture of CO and VOCs. The purpose of this
study is to investigate the alumina supported copper-manganese
catalysts with different Cu/Mn molar ratio in terms of oxidation of
CO, methanol and dimethyl ether. The catalysts were prepared by impregnation of γ-Al2O3 with
copper and manganese nitrates and the catalytic activity
measurements were carried out in two stage continuous flow
equipment with an adiabatic reactor for simultaneous oxidation of all
compounds under the conditions closest possible to the industrial. Gas
mixtures on the input and output of the reactor were analyzed with a
gas chromatograph, equipped with FID and TCD detectors. The
texture characteristics were determined by low-temperature (- 196oС)
nitrogen adsorption in a Quantachrome Instruments NOVA 1200e
(USA) specific surface area & pore analyzer. Thermal, XRD and
TPR analyses were performed. It was established that the active component of the mixed Cu-
Mn/γ–alumina catalysts strongly depends on the Cu/Mn molar ratio.
Highly active alumina supported Cu-Mn catalysts for CO, methanol
and DME oxidation were synthesized. While the hopcalite is the best
catalyst for CO oxidation, the best compromise for simultaneous
oxidation of all components is the catalyst with Cu/Mn molar ratio
1:5.