Abstract: Bagging and boosting are among the most popular re-sampling ensemble methods that generate and combine a diversity of regression models using the same learning algorithm as base-learner. Boosting algorithms are considered stronger than bagging on noise-free data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using an averaging methodology of bagging and boosting ensembles with 10 sub-learners in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-learners on standard benchmark datasets and the proposed ensemble gave better accuracy.
Abstract: In this paper, we consider a multi user multiple input
multiple output (MU-MIMO) based cooperative reporting system for
cognitive radio network. In the reporting network, the secondary
users forward the primary user data to the common fusion center
(FC). The FC is equipped with linear equalizers and an energy
detector to make the decision about the spectrum. The primary user
data are considered to be a digital video broadcasting - terrestrial
(DVB-T) signal. The sensing channel and the reporting channel are
assumed to be an additive white Gaussian noise and an independent
identically distributed Raleigh fading respectively. We analyzed the
detection probability of MU-MIMO system with linear equalizers and
arrived at the closed form expression for average detection
probability. Also the system performance is investigated under
various MIMO scenarios through Monte Carlo simulations.
Abstract: This paper proposes a novel feature extraction method,
based on Discrete Wavelet Transform (DWT) and K-L Seperability
(KLS), for the classification of Functional Data (FD). This method
combines the decorrelation and reduction property of DWT and the
additive independence property of KLS, which is helpful to extraction
classification features of FD. It is an advanced approach of the
popular wavelet based shrinkage method for functional data reduction
and classification. A theory analysis is given in the paper to prove the
consistent convergence property, and a simulation study is also done
to compare the proposed method with the former shrinkage ones. The
experiment results show that this method has advantages in improving
classification efficiency, precision and robustness.
Abstract: Zinc borates can be used as multi-functional
synergistic additives with flame retardant additives in polymers. Zinc
borate is white, non-hygroscopic and powder type product. The most
important properties are low solubility in water and high dehydration
temperature. Zinc borates dehydrate above 290°C and anhydrous zinc
borate has thermal resistance about 400°C. Zinc borates can be
synthesized using several methods such as hydrothermal and solidstate
processes. In this study, the solid-state method was applied at
low temperatures of 600oC and 700oC using the starting materials of
ZnO and H3BO3 with several mole ratios. The reaction time was
determined as 4 hours after some preliminary experiments. After the
synthesis, the crystal structure and the morphology of the products
were examined by X-Ray Diffraction (XRD) and Fourier Transform
Infrared Spectroscopy (FT-IR). As a result the forms of ZnB4O7,
Zn3(BO3)2, ZnB2O4 were synthesized and obtained along with the
unreacted ZnO.
Abstract: There was a high rate of corrosion in Pyrolysis
Gasoline Hydrogenation (PGH) unit of Arak Petrochemical Company
(ARPC), and it caused some operational problem in this plant. A
commercial chemical had been used as anti-corrosion in the
depentanizer column overhead in order to control the corrosion rate.
Injection of commercial corrosion inhibitor caused some
operational problems such as fouling in some heat exchangers. It was
proposed to replace this commercial material with another more
effective trouble free, and well-known additive by R&D and
operation specialists.
At first, the system was simulated by commercial simulation
software in electrolytic system to specify low pH points inside the
plant. After a very comprehensive study of the situation and technical
investigations ,ammonia / monoethanol amine solution was proposed
as neutralizer or corrosion inhibitor to be injected in a suitable point
of the plant. For this purpose, the depentanizer column and its
accessories system was simulated again in case of this solution
injection.
According to the simulation results, injection of new anticorrosion
substance has no any side effect on C5 cut product and
operating conditions of the column. The corrosion rate will be
cotrolled, if the pH remains at the range of 6.5 to 8 . Aactual plant
test run was also carried out by injection of ammonia / monoethanol
amine solution at the rate of 0.6 Kg/hr and the results of iron content
of water samples and corrosion test coupons confirmed the
simulation results.
Now, ammonia / monoethanol amine solution is injected to a
suitable pint inside the plant and corrosion rate has decreased
significantly.
Abstract: The paper presents frame and burst acquisition in a satellite communication network based on time division multiple access (TDMA) in which the transmissions may be carried on different transponders. A unique word pattern is used for the acquisition process. The search for the frame is aided by soft-decision of QPSK modulated signals in an additive white Gaussian channel. Results show that when the false alarm rate is low the probability of detection is also low, and the acquisition time is long. Conversely when the false alarm rate is high, the probability of detection is also high and the acquisition time is short. Thus the system operators can trade high false alarm rates for high detection probabilities and shorter acquisition times.
Abstract: The study of effect of laser scanning speed on
material efficiency in Ti6Al4V application is very important because unspent powder is not reusable because of high temperature oxygen
pick-up and contamination. This study carried out an extensive study
on the effect of scanning speed on material efficiency by varying the
speed between 0.01 to 0.1m/sec. The samples are wire brushed and
cleaned with acetone after each deposition to remove un-melted
particles from the surface of the deposit. The substrate is weighed before and after deposition. A formula was developed to calculate the
material efficiency and the scanning speed was compared with the
powder efficiency obtained. The results are presented and discussed.
The study revealed that the optimum scanning speed exists for this study at 0.01m/sec, above and below which the powder efficiency
will drop
Abstract: Webcam systems now function as the new privileged
vantage points from which to view the city. This transformation of
CCTV technology from surveillance to promotional tool is significant
because its'scopic regime' presents, back to the public, a new virtual
'site' that sits alongside its real-time counterpart. Significantly,
thisraw 'image' data can, in fact,be co-optedand processed so as to
disrupt their original purpose. This paper will demonstrate this
disruptive capacity through an architectural project. It will reveal how
the adaption the webcam image offers a technical springboard by
which to initiate alternate urban form making decisions and subvert
the disciplinary reliance on the 'flat' orthographic plan. In so doing,
the paper will show how this 'digital material' exceeds the imagistic
function of the image; shiftingit from being a vehicle of signification
to a site of affect.
Abstract: In this paper, the performance of three types of serial
concatenated convolutional codes (SCCC) is compared and analyzed
in additive white Gaussian noise (AWGN) channel. In Type I, only the
parity bits of outer encoder are passed to inner encoder. In Type II and
Type III, both the information bits and the parity bits of outer encoder
are transferred to inner encoder. As results of simulation, Type I shows
the best bit error rate (BER) performance at low signal-to-noise ratio
(SNR). On the other hand, Type III shows the best BER performance
at high SNR in AWGN channel. The simulation results are analyzed
using the distance spectrum.
Abstract: A systematic and exhaustive method based on the group
structure of a unitary Lie algebra is proposed to generate an enormous
number of quantum codes. With respect to the algebraic structure,
the orthogonality condition, which is the central rule of generating
quantum codes, is proved to be fully equivalent to the distinguishability
of the elements in this structure. In addition, four types of
quantum codes are classified according to the relation of the codeword
operators and some initial quantum state. By linking the unitary Lie
algebra with the additive group, the classical correspondences of some
of these quantum codes can be rendered.
Abstract: Support Vector Machine (SVM) is a recent class of statistical classification and regression techniques playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM is applied to an infrared (IR) binary communication system with different types of channel models including Ricean multipath fading and partially developed scattering channel with additive white Gaussian noise (AWGN) at the receiver. The structure and performance of SVM in terms of the bit error rate (BER) metric is derived and simulated for these channel stochastic models and the computational complexity of the implementation, in terms of average computational time per bit, is also presented. The performance of SVM is then compared to classical binary signal maximum likelihood detection using a matched filter driven by On-Off keying (OOK) modulation. We found that the performance of SVM is superior to that of the traditional optimal detection schemes used in statistical communication, especially for very low signal-to-noise ratio (SNR) ranges. For large SNR, the performance of the SVM is similar to that of the classical detectors. The implication of these results is that SVM can prove very beneficial to IR communication systems that notoriously suffer from low SNR at the cost of increased computational complexity.
Abstract: The increased number of automobiles in recent years
has resulted in great demand for fossil fuel. This has led to the
development of automobile by using alternative fuels which include
gaseous fuels, biofuels and vegetables oils as fuel. Energy from
biomass and more specific bio-diesel is one of the opportunities that
could cover the future demand of fossil fuel shortage. Biomass in the
form of cashew nut shell represents a new energy source and
abundant source of energy in India. The bio-fuel is derived from
cashew nut shell oil and its blend with diesel are promising
alternative fuel for diesel engine. In this work the pyrolysis Cashew
Nut Shell Liquid (CNSL)-Diesel Blends (CDB) was used to run the
Direct Injection (DI) diesel engine. The experiments were conducted
with various blends of CNSL and Diesel namely B20, B40, B60, B80
and B100. The results are compared with neat diesel operation. The
brake thermal efficiency was decreased for blends of CNSL and
Diesel except the lower blends of B20. The brake thermal efficiency
of B20 is nearly closer to that of diesel fuel. Also the emission level
of the all CNSL and Diesel blends was increased compared to neat
diesel. The higher viscosity and lower volatility of CNSL leads to
poor mixture formation and hence lower brake thermal efficiency and
higher emission levels. The higher emission level can be reduced by
adding suitable additives and oxygenates with CNSL and Diesel
blends.
Abstract: This work deals with unsupervised image deblurring.
We present a new deblurring procedure on images provided by lowresolution
synthetic aperture radar (SAR) or simply by multimedia in
presence of multiplicative (speckle) or additive noise, respectively.
The method we propose is defined as a two-step process. First, we
use an original technique for noise reduction in wavelet domain.
Then, the learning of a Kohonen self-organizing map (SOM) is
performed directly on the denoised image to take out it the blur. This
technique has been successfully applied to real SAR images, and the
simulation results are presented to demonstrate the effectiveness of
the proposed algorithms.
Abstract: Laser Metal Deposition (LMD) is an additive manufacturing process with capabilities that include: producing new
part directly from 3 Dimensional Computer Aided Design (3D CAD)
model, building new part on the existing old component and repairing an existing high valued component parts that would have
been discarded in the past. With all these capabilities and its advantages over other additive manufacturing techniques, the
underlying physics of the LMD process is yet to be fully understood probably because of high interaction between the processing
parameters and studying many parameters at the same time makes it
further complex to understand. In this study, the effect of laser power
and powder flow rate on physical properties (deposition height and
deposition width), metallurgical property (microstructure) and
mechanical (microhardness) properties on laser deposited most
widely used aerospace alloy are studied. Also, because the Ti6Al4V
is very expensive, and LMD is capable of reducing buy-to-fly ratio
of aerospace parts, the material utilization efficiency is also studied.
Four sets of experiments were performed and repeated to establish repeatability using laser power of 1.8 kW and 3.0 kW, powder flow
rate of 2.88 g/min and 5.67 g/min, and keeping the gas flow rate and
scanning speed constant at 2 l/min and 0.005 m/s respectively. The
deposition height / width are found to increase with increase in laser
power and increase in powder flow rate. The material utilization is favoured by higher power while higher powder flow rate reduces
material utilization. The results are presented and fully discussed.
Abstract: In this paper a novel method for multiple one dimensional real valued sinusoidal signal frequency estimation in the presence of additive Gaussian noise is postulated. A computationally simple frequency estimation method with efficient statistical performance is attractive in many array signal processing applications. The prime focus of this paper is to combine the subspace-based technique and a simple peak search approach. This paper presents a variant of the Propagator Method (PM), where a collaborative approach of SUMWE and Propagator method is applied in order to estimate the multiple real valued sine wave frequencies. A new data model is proposed, which gives the dimension of the signal subspace is equal to the number of frequencies present in the observation. But, the signal subspace dimension is twice the number of frequencies in the conventional MUSIC method for estimating frequencies of real-valued sinusoidal signal. The statistical analysis of the proposed method is studied, and the explicit expression of asymptotic (large-sample) mean-squared-error (MSE) or variance of the estimation error is derived. The performance of the method is demonstrated, and the theoretical analysis is substantiated through numerical examples. The proposed method can achieve sustainable high estimation accuracy and frequency resolution at a lower SNR, which is verified by simulation by comparing with conventional MUSIC, ESPRIT and Propagator Method.
Abstract: Support Vector Machine (SVM) is a statistical
learning tool developed to a more complex concept of
structural risk minimization (SRM). In this paper, SVM is
applied to signal detection in communication systems in the
presence of channel noise in various environments in the form
of Rayleigh fading, additive white Gaussian background noise
(AWGN), and interference noise generalized as additive color
Gaussian noise (ACGN). The structure and performance of
SVM in terms of the bit error rate (BER) metric is derived and
simulated for these advanced stochastic noise models and the
computational complexity of the implementation, in terms of
average computational time per bit, is also presented. The
performance of SVM is then compared to conventional binary
signaling optimal model-based detector driven by binary
phase shift keying (BPSK) modulation. We show that the
SVM performance is superior to that of conventional matched
filter-, innovation filter-, and Wiener filter-driven detectors,
even in the presence of random Doppler carrier deviation,
especially for low SNR (signal-to-noise ratio) ranges. For
large SNR, the performance of the SVM was similar to that of
the classical detectors. However, the convergence between
SVM and maximum likelihood detection occurred at a higher
SNR as the noise environment became more hostile.
Abstract: This paper presents an approach for an unequal error
protection of facial features of personal ID images coding. We
consider unequal error protection (UEP) strategies for the efficient
progressive transmission of embedded image codes over noisy
channels. This new method is based on the progressive image
compression embedded zerotree wavelet (EZW) algorithm and UEP
technique with defined region of interest (ROI). In this case is ROI
equal facial features within personal ID image. ROI technique is
important in applications with different parts of importance. In ROI
coding, a chosen ROI is encoded with higher quality than the
background (BG). Unequal error protection of image is provided by
different coding techniques and encoding LL band separately. In our
proposed method, image is divided into two parts (ROI, BG) that
consist of more important bytes (MIB) and less important bytes
(LIB). The proposed unequal error protection of image transmission
has shown to be more appropriate to low bit rate applications,
producing better quality output for ROI of the compresses image.
The experimental results verify effectiveness of the design. The
results of our method demonstrate the comparison of the UEP of
image transmission with defined ROI with facial features and the
equal error protection (EEP) over additive white gaussian noise
(AWGN) channel.
Abstract: We successfully developed a new straw combustion
technology that efficiently reduces problems with unmanageable deposits inside straw fueled boilers in Zluticka Heating Plant. The
deposits are mainly created by glass-forming melts. We plotted straw compositions in K2O-CaO-SiO2 phase diagram and illustrated
they are in the area of low-melting eutectic poi
melting of ash and the formation of deposits
compositions by injecting additives into biomass fuel
ueled points. To prevent the
deposits, we modified ash
fuel.
Abstract: We consider optimal channel equalization for MIMO
(multi-input/multi-output) time-varying channels in the sense of
MMSE (minimum mean-squared-error), where the observation noise
can be non-stationary. We show that all ZF (zero-forcing) receivers
can be parameterized in an affine form which eliminates completely
the ISI (inter-symbol-interference), and optimal channel equalizers
can be designed through minimization of the MSE (mean-squarederror)
between the detected signals and the transmitted signals,
among all ZF receivers. We demonstrate that the optimal channel
equalizer is a modified Kalman filter, and show that under the AWGN
(additive white Gaussian noise) assumption, the proposed optimal
channel equalizer minimizes the BER (bit error rate) among all
possible ZF receivers. Our results are applicable to optimal channel
equalization for DWMT (discrete wavelet multitone), multirate transmultiplexers,
OFDM (orthogonal frequency division multiplexing),
and DS (direct sequence) CDMA (code division multiple access)
wireless data communication systems. A design algorithm for optimal
channel equalization is developed, and several simulation examples
are worked out to illustrate the proposed design algorithm.
Abstract: Non-saturated soils that while saturation greatly
decrease their volume, have sudden settlement due to increasing
humidity, fracture and structural crack are called loess soils. Whereas
importance of civil projects including: dams, canals and
constructions bearing this type of soil and thereof problems, it is
required for carrying out more research and study in relation to loess
soils. This research studies shear strength parameters by using
grading test, Atterberg limit, compression, direct shear and
consolidation and then effect of using cement and lime additives on
stability of loess soils is studied. In related tests, lime and cement are
separately added to mixed ratios under different percentages of soil
and for different times the stabilized samples are processed and effect
of aforesaid additives on shear strength parameters of soil is studied.
Results show that upon passing time the effect of additives and
collapsible potential is greatly decreased and upon increasing
percentage of cement and lime the maximum dry density is
decreased; however, optimum humidity is increased. In addition,
liquid limit and plastic index is decreased; however, plastic index
limit is increased. It is to be noted that results of direct shear test
reveal increasing shear strength of soil due to increasing cohesion
parameter and soil friction angle.