Abstract: In this paper, we consider the MU-MISO downlink scenario, under imperfect channel state information (CSI). The main issue in imperfect CSI is to keep the probability of each user achievable outage rate below the given threshold level. Such a rate outage constraints present significant and analytical challenges. There are many probabilistic methods are used to minimize the transmit optimization problem under imperfect CSI. Here, decomposition based large deviation inequality and Bernstein type inequality convex restriction methods are used to perform the optimization problem under imperfect CSI. These methods are used for achieving improved output quality and lower complexity. They provide a safe tractable approximation of the original rate outage constraints. Based on these method implementations, performance has been evaluated in the terms of feasible rate and average transmission power. The simulation results are shown that all the two methods offer significantly improved outage quality and lower computational complexity.
Abstract: A methodology based on wavelets is proposed for the automatic location and delimitation of defects in limestone plates. Natural defects include dark colored spots, crystal zones trapped in the stone, areas of abnormal contrast colors, cracks or fracture lines, and fossil patterns. Although some of these may or may not be considered as defects according to the intended use of the plate, the goal is to pair each stone with a map of defects that can be overlaid on a computer display. These layers of defects constitute a database that will allow the preliminary selection of matching tiles of a particular variety, with specific dimensions, for a requirement of N square meters, to be done on a desktop computer rather than by a two-hour search in the storage park, with human operators manipulating stone plates as large as 3 m x 2 m, weighing about one ton. Accident risks and work times are reduced, with a consequent increase in productivity. The base for the algorithm is wavelet decomposition executed in two instances of the original image, to detect both hypotheses – dark and clear defects. The existence and/or size of these defects are the gauge to classify the quality grade of the stone products. The tuning of parameters that are possible in the framework of the wavelets corresponds to different levels of accuracy in the drawing of the contours and selection of the defects size, which allows for the use of the map of defects to cut a selected stone into tiles with minimum waste, according the dimension of defects allowed.
Abstract: Fenton oxidation technology is the general strategy for the treatment of organic compounds-contained wastewater. However, a considerable amount of ferric sludge was produced during the Fenton process as secondary wastes, which were needed to be further removed from the effluent and treated. In this study, heterogeneous catalysts based on ferrite oxide (Cu-Fe-Ce-O) were synthesized and characterized, and their application for Fenton-like oxidation of simulated and actual radioactive organic wastewater was investigated. The results of TOC decomposition efficiency around 54% ~ 99% were obtained when the catalyst loading, H2O2 loading, pH, temperature, and reaction time were controlled. In this case, no secondary wastes formed and the given catalysts were able to be separated by magnetic devices and reused again.
Abstract: Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.
Abstract: In this work, the system evaluates the impact of considering a stochastic approach on the day ahead basis Unit Commitment. Comparisons between stochastic and deterministic Unit Commitment solutions are provided. The Unit Commitment model consists in the minimization of the total operation costs considering unit’s technical constraints like ramping rates, minimum up and down time. Load shedding and wind power spilling is acceptable, but at inflated operational costs. The evaluation process consists in the calculation of the optimal unit commitment and in verifying the fulfillment of the considered constraints. For the calculation of the optimal unit commitment, an algorithm based on the Benders Decomposition, namely on the Dual Dynamic Programming, was developed. Two approaches were considered on the construction of stochastic solutions. Data related to wind power outputs from two different operational days are considered on the analysis. Stochastic and deterministic solutions are compared based on the actual measured wind power output at the operational day. Through a technique capability of finding representative wind power scenarios and its probabilities, the system can analyze a more detailed process about the expected final operational cost.
Abstract: This paper uses a primary data from 670 Chinese
manufacturing firms, together with the newly introduced regressionbased
inequality decomposition method, to study the effect of
openness on wage inequality. We find that openness leads to a
positive industry wage premium, but its contribution to firm-level
wage inequality is relatively small, only 4.69%. The major
contributor to wage inequality is human capital, which could explain
14.3% of wage inequality across sample firms.
Abstract: In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.
Abstract: This study was conducted for the investigation of
number of cellulolytic bacteria and their ability in decomposition.
Seven samples surface soil were collected on cellulose Zailiskii
Alatau slopes. Cellulolitic activity of new strains of Bacillus, isolated
from soil is determined. Isolated cellulose degrading bacteria were
screened for determination of the highest cellulose activity by
quantitative assay using Congo red, gravimetric assay and
colorimetric DNS method trough of the determination of the
parameters of sugar reduction. Strains are assigned to: B.subtilis,
B.licheniformis, B. cereus and, В. megaterium. Bacillus strains
consisting of several different types of cellulases have broad substrate
specificity of cellulase complexes formed by them. Cellulolitic
bacteria were recorded to have highest cellulase activity and selected
for optimization of cellulase enzyme production.
Abstract: The source of the jet noise is generated by rocket exhaust plume during rocket engine testing. A domain decomposition approach is applied to the jet noise prediction in this paper. The aerodynamic noise coupling is based on the splitting into acoustic sources generation and sound propagation in separate physical domains. Large Eddy Simulation (LES) is used to simulate the supersonic jet flow. Based on the simulation results of the flow-fields, the jet noise distribution of the sound pressure level is obtained by applying the Ffowcs Williams-Hawkings (FW-H) acoustics equation and Fourier transform. The calculation results show that the complex structures of expansion waves, compression waves and the turbulent boundary layer could occur due to the strong interaction between the gas jet and the ambient air. In addition, the jet core region, the shock cell and the sound pressure level of the gas jet increase with the nozzle size increasing. Importantly, the numerical simulation results of the far-field sound are in good agreement with the experimental measurements in directivity.
Abstract: With 40% of total world energy consumption,
building systems are developing into technically complex large
energy consumers suitable for application of sophisticated power
management approaches to largely increase the energy efficiency
and even make them active energy market participants. Centralized
control system of building heating and cooling managed by
economically-optimal model predictive control shows promising
results with estimated 30% of energy efficiency increase. The research
is focused on implementation of such a method on a case study
performed on two floors of our faculty building with corresponding
sensors wireless data acquisition, remote heating/cooling units and
central climate controller. Building walls are mathematically modeled
with corresponding material types, surface shapes and sizes. Models
are then exploited to predict thermal characteristics and changes in
different building zones. Exterior influences such as environmental
conditions and weather forecast, people behavior and comfort
demands are all taken into account for deriving price-optimal climate
control. Finally, a DC microgrid with photovoltaics, wind turbine,
supercapacitor, batteries and fuel cell stacks is added to make the
building a unit capable of active participation in a price-varying
energy market. Computational burden of applying model predictive
control on such a complex system is relaxed through a hierarchical
decomposition of the microgrid and climate control, where the
former is designed as higher hierarchical level with pre-calculated
price-optimal power flows control, and latter is designed as lower
level control responsible to ensure thermal comfort and exploit
the optimal supply conditions enabled by microgrid energy flows
management. Such an approach is expected to enable the inclusion
of more complex building subsystems into consideration in order to
further increase the energy efficiency.
Abstract: Torrefaction of biomass pellets is considered as a
useful pretreatment technology in order to convert them into a high
quality solid biofuel that is more suitable for pyrolysis, gasification,
combustion, and co-firing applications. In the course of torrefaction,
the temperature varies across the pellet, and therefore chemical
reactions proceed unevenly within the pellet. However, the
uniformity of the thermal distribution along the pellet is generally
assumed. The torrefaction process of a single cylindrical pellet is
modeled here, accounting for heat transfer coupled with chemical
kinetics. The drying sub-model was also introduced. The nonstationary
process of wood pellet decomposition is described by the
system of non-linear partial differential equations over the
temperature and mass. The model captures well the main features of
the experimental data.
Abstract: Digital images are widely used in computer
applications. To store or transmit the uncompressed images
requires considerable storage capacity and transmission bandwidth.
Image compression is a means to perform transmission or storage of
visual data in the most economical way. This paper explains about
how images can be encoded to be transmitted in a multiplexing
time-frequency domain channel. Multiplexing involves packing
signals together whose representations are compact in the working
domain. In order to optimize transmission resources each 4 × 4
pixel block of the image is transformed by a suitable polynomial
approximation, into a minimal number of coefficients. Less than
4 × 4 coefficients in one block spares a significant amount of
transmitted information, but some information is lost. Different
approximations for image transformation have been evaluated as
polynomial representation (Vandermonde matrix), least squares +
gradient descent, 1-D Chebyshev polynomials, 2-D Chebyshev
polynomials or singular value decomposition (SVD). Results have
been compared in terms of nominal compression rate (NCR),
compression ratio (CR) and peak signal-to-noise ratio (PSNR)
in order to minimize the error function defined as the difference
between the original pixel gray levels and the approximated
polynomial output. Polynomial coefficients have been later encoded
and handled for generating chirps in a target rate of about two
chirps per 4 × 4 pixel block and then submitted to a transmission
multiplexing operation in the time-frequency domain.
Abstract: An experimental study with four different types of bed
conditions was carried out to understand the effect of roughness in
open channel flow at two different Reynolds numbers. The bed
conditions include a smooth surface and three different roughness
conditions, which were generated using sand grains with a median
diameter of 2.46 mm. The three rough conditions include a surface
with distributed roughness, a surface with continuously distributed
roughness and a sand bed with a permeable interface. A commercial
two-component fibre-optic LDA system was used to conduct the
velocity measurements. The variables of interest include the mean
velocity, turbulence intensity, correlation between the streamwise and
the wall normal turbulence, Reynolds shear stress and velocity triple
products. Quadrant decomposition was used to extract the magnitude
of the Reynolds shear stress of the turbulent bursting events. The
effect of roughness was evident throughout the flow depth. The
results show that distributed roughness has the greatest roughness
effect followed by the sand bed and the continuous roughness.
Compared to the smooth bed, the streamwise turbulence intensity
reduces but the vertical turbulence intensity increases at a location
very close to the bed due to the introduction of roughness. Although
the same sand grain is used to create the three different rough bed
conditions, the difference in the turbulence intensity is an indication
that the specific geometry of the roughness has an influence on
turbulence structure.
Abstract: This paper describes a subarray based low
computational design method of multiuser massive multiple
input multiple output (MIMO) system. In our previous works, use of
large array is assumed only in transmitter, but this study considers
the case both of transmitter and receiver sides are equipped with
large array antennas. For this aim, receive arrays are also divided
into several subarrays, and the former proposed method is modified
for the synthesis of a large array from subarrays in both ends.
Through computer simulations, it is verified that the performance
of the proposed method is degraded compared with the original
approach, but it can achieve the improvement in the aspect of
complexity, namely, significant reduction of the computational load
to the practical level.
Abstract: Singular value decomposition based optimisation of
geometric design parameters of a 5-speed gearbox is studied. During
the optimisation, a four-degree-of freedom torsional vibration model
of the pinion gear-wheel gear system is obtained and the minimum
singular value of the transfer matrix is considered as the objective
functions. The computational cost of the associated singular value
problems is quite low for the objective function, because it is only
necessary to compute the largest and smallest singular values (μmax
and μmin) that can be achieved by using selective eigenvalue solvers;
the other singular values are not needed. The design parameters are
optimised under several constraints that include bending stress,
contact stress and constant distance between gear centres. Thus, by
optimising the geometric parameters of the gearbox such as, the
module, number of teeth and face width it is possible to obtain a
light-weight-gearbox structure. It is concluded that the all optimised
geometric design parameters also satisfy all constraints.
Abstract: Biodiesel is one of the alternative fuels that promising
for substituting petro diesel as energy source which is advantage on
sustainability and ecofriendly. Due to the raw material that tend to
decompose during storage, biodiesel also have the same characteristic
that tend to decompose and formed higher acid value which is the
result of oxidation to double bond on a chain of ester. Decomposition of biodiesel due to oxidation reaction could
prevent by introduce a small amount of antioxidant. The origin of raw
materials and the process for producing biodiesel will determine the
effectiveness of antioxidant. The quality degradation on biodiesel
could evaluate by measuring iodine value and acid number of
biodiesel. Biodiesel made from high fatty acid Jatropha curcas oil by using
esterification and transesterification process will stand on the quality
by introduce 90 ppm pyrogallol powder on the biodiesel, which could
increase Induction period time from 2 hours to more than 6 hours in
rancimat test evaluation.
Abstract: Polyaniline is an indispensible component in lightemitting
devices (LEDs), televisions, cellular telephones, automotive,
corrosion-resistant coatings, actuators etc. The electrical conductivity
properties was found be increased by introduction of metal nano
particles. In the present study, an attempt has been made to utilize
platinum nano particles to achieve the improved electrical properties.
Polyaniline and Pt-polyaniline composite are synthesized by
electrochemical routes. X-ray diffractometer confirms the amorphous
nature of polyaniline. The Bragg’s diffraction peaks correspond to
platinum nanoparticles in Pt-polyaniline composite and
thermogravimetric analyzer indicates its decomposition at certain
temperature. The Scanning Electron Micrographs of colloidal
platinum nanoparticles were spherical, uniform shape in the
composite. The current-voltage (I-V) characteristics of the PANI and
composites were also studied which indicate a significant decreasing
resistivity than PANI-Platinum after introduction of pt nanoparticles
in the matrix of polyaniline (PANI).
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: The paper provides a comprehensive analysis of the
sustainable development in the Belgrade Metropolitan Region - BMA
(level NUTS 2) preliminary evaluating the three chosen components:
1) economic growth and developmental changes; 2) competitiveness;
and 3) territorial concentration and industrial specialization. First, we
identified the main results of development changes and economic
growth by applying Shift-share analysis on the metropolitan level.
Second, the empirical evaluation of competitiveness in the BMA is
based on the analysis of absolute and relative values of eight
indicators by Spider method. Paper shows that the consideration of
the national share, industrial mix and metropolitan/regional share in
total Shift share of the BMA, as well as economic/functional
specialization of the BMA indicate very strong process of
deindustrialization. Allocative component of the BMA economic
growth has positive value, reflecting the above-average sector
productivity compared to the national average. Third, the important
positive role of metropolitan/regional component in decomposition of
the BMA economic growth is highlighted as one of the key results.
Finally, comparative analysis of the industrial territorial
concentration in the BMA in relation to Serbia is based on location
quotient (LQ) or Balassa index as a valid measure. The results
indicate absolute and relative differences in decrease of industry
territorial concentration as well as inefficiency of utilizing territorial
capital in the BMA. Results are important for the increase of regional
competitiveness and territorial distribution in this area as well as for
improvement of sustainable metropolitan and sector policies,
planning and governance on this level.
Abstract: Due to the resultant leachate from waste
decomposition in landfills has polluter potential hundred times
greater than domestic sewage, this is considered a problem related to
the depreciation of environment requiring pre-disposal treatment.In
seeking to improve this situation, this project proposes the treatment
of landfill leachate using natural fibers intercropped with advanced
oxidation processes. The selected natural fibers were palm, coconut
and banana fiber.These materials give sustainability to the project
because, besides having adsorbent capacity, are often part of waste
discarded. The study was conducted in laboratory scale.In trials, the
effluents were characterized as Chemical Oxygen Demand (COD),
Turbidity and Color. The results indicate that is technically
promising since that there were extremely oxidative conditions, the
use of certain natural fibers in the reduction of pollutants in leachate
have been obtained results of COD removals between 67.9% and
90.9%, Turbidity between 88.0% and 99.7% and Color between
67.4% and 90.4%.The expectation generated is to continue evaluating
the association of efficiency of other natural fibers with other landfill
leachate treatment processes.