Abstract: Data stream analysis is the process of computing
various summaries and derived values from large amounts of data
which are continuously generated at a rapid rate. The nature of a
stream does not allow a revisit on each data element. Furthermore,
data processing must be fast to produce timely analysis results. These
requirements impose constraints on the design of the algorithms to
balance correctness against timely responses. Several techniques
have been proposed over the past few years to address these
challenges. These techniques can be categorized as either dataoriented
or task-oriented. The data-oriented approach analyzes a
subset of data or a smaller transformed representation, whereas taskoriented
scheme solves the problem directly via approximation
techniques. We propose a hybrid approach to tackle the data stream
analysis problem. The data stream has been both statistically
transformed to a smaller size and computationally approximated its
characteristics. We adopt a Monte Carlo method in the approximation
step. The data reduction has been performed horizontally and
vertically through our EMR sampling method. The proposed method
is analyzed by a series of experiments. We apply our algorithm on
clustering and classification tasks to evaluate the utility of our
approach.
Abstract: This paper presents Faults Forecasting System (FFS)
that utilizes statistical forecasting techniques in analyzing process
variables data in order to forecast faults occurrences. FFS is
proposing new idea in detecting faults. Current techniques used in
faults detection are based on analyzing the current status of the
system variables in order to check if the current status is fault or not.
FFS is using forecasting techniques to predict future timing for faults
before it happens. Proposed model is applying subset modeling
strategy and Bayesian approach in order to decrease dimensionality
of the process variables and improve faults forecasting accuracy. A
practical experiment, designed and implemented in Okayama
University, Japan, is implemented, and the comparison shows that
our proposed model is showing high forecasting accuracy and
BEFORE-TIME.
Abstract: In this paper first, Two buildings have been modeled
and then analyzed using nonlinear static analysis method under two
different conditions in Nonlinear SAP 2000 software. In the first
condition the interaction of soil adjacent to the walls of basement are
ignored while in the second case this interaction have been modeled
using Gap elements of nonlinear SAP2000 software. Finally,
comparing the results of two models, the effects of soil-structure on
period, target point displacement, internal forces, shape deformations
and base shears have been studied. According to the results, this
interaction has always increased the base shear of buildings,
decreased the period of structure and target point displacement, and
often decreased the internal forces and displacements.
Abstract: A geothermal power plant multiple simulator for
operators training is presented. The simulator is designed to be
installed in a wireless local area network and has a capacity to train
one to six operators simultaneously, each one with an independent
simulation session. The sessions must be supervised only by one
instructor. The main parts of this multiple simulator are: instructor
and operator-s stations. On the instructor station, the instructor
controls the simulation sessions, establishes training exercises and
supervises each power plant operator in individual way. This station
is hosted in a Main Personal Computer (NS) and its main functions
are: to set initial conditions, snapshots, malfunctions or faults,
monitoring trends, and process and soft-panel diagrams. On the other
hand the operators carry out their actions over the power plant
simulated on the operator-s stations; each one is also hosted in a PC.
The main software of instructor and operator-s stations are executed
on the same NS and displayed in PCs through graphical Interactive
Process Diagrams (IDP). The geothermal multiple simulator has been
installed in the Geothermal Simulation Training Center (GSTC) of
the Comisi├│n Federal de Electricidad, (Federal Commission of
Electricity, CFE), Mexico, and is being utilized as a part of the
training courses for geothermal power plant operators.
Abstract: The inability to implement the principles of good
corporate governance (GCG) as demonstrated in the surveys is due to
a number of constraints which can be classified into three; namely internal constraints, external constraints, and constraints coming
from the structure of ownership. The issues in the internal constraints
mentioned are related to the function of several elements of the company. As a business organization, corporation is unable to
achieve its goal to successfully implement GCG principles since it is
not support by its internal elements- functions. Two of several numbers of internal elements of a company are ethical work climate
and leadership style of the top management.
To prove the correlation between internal function of organization
(in this case ethical work climate and transformational leadership)
and the successful implementation of GCG principles, this study
proposes two hypotheses to be empirically tested on thirty surveyed organizations; eleven of which are state-owned companies and
nineteen are private companies. These thirty corporations are listed in
the Jakarta Stock Exchange. All state-owned companies in the
samples are those which have been privatized.
The research showed that internal function of organization give
support to the successful implementation of GCG principle. In this
research we can prove that : (i) ethical work climate has positive
significance of correlation with the successful implementation of
social awareness principle (one of principles on GCG) and, (ii) only
at the state-owned companies, transformational leadership have
positive significance effect to forming the ethical work climate.
Abstract: The control of commutation of switched reluctance
(SR) motor has nominally depended on a physical position detector.
The physical rotor position sensor limits robustness and increases
size and inertia of the SR drive system. The paper describes a method
to overcome these limitations by using magnetization characteristics
of the motor to indicate rotor and stator teeth overlap status. The
method is using active current probing pulses of same magnitude that
is used to simulate flux linkage in the winding being probed. A
microprocessor is used for processing magnetization data to deduce
rotor-stator teeth overlap status and hence rotor position. However,
the back-of-core saturation and mutual coupling introduces overlap
detection errors, hence that of commutation control. This paper
presents the concept of the detection scheme and the effects of backof
core saturation.
Abstract: The spectral action balance equation is an equation that
used to simulate short-crested wind-generated waves in shallow water
areas such as coastal regions and inland waters. This equation consists
of two spatial dimensions, wave direction, and wave frequency which
can be solved by finite difference method. When this equation with
dominating propagation velocity terms are discretized using central
differences, stability problems occur when the grid spacing is chosen
too coarse. In this paper, we introduce the splitting modified donorcell
scheme for avoiding stability problems and prove that it is
consistent to the modified donor-cell scheme with same accuracy. The
splitting modified donor-cell scheme was adopted to split the wave
spectral action balance equation into four one-dimensional problems,
which for each small problem obtains the independently tridiagonal
linear systems. For each smaller system can be solved by direct or
iterative methods at the same time which is very fast when performed
by a multi-cores computer.
Abstract: To successfully provide a fast FIR filter with FTT algorithms, overlapped-save algorithms can be used to lower the computational complexity and achieve the desired real-time processing. As the length of the input block increases in order to improve the efficiency, a larger volume of zero padding will greatly increase the computation length of the FFT. In this paper, we use the overlapped block digital filtering to construct a parallel structure. As long as the down-sampling (or up-sampling) factor is an exact multiple lengths of the impulse response of a FIR filter, we can process the input block by using a parallel structure and thus achieve a low-complex fast FIR filter with overlapped-save algorithms. With a long filter length, the performance and the throughput of the digital filtering system will also be greatly enhanced.
Abstract: Sample of CsAg2I3 was prepared by solid state reaction. Then, microstructure parameters of this sample have been determined using wide angle X-ray scattering WAXS method. As well as, Cell parameters of crystal structure have been refined using CHEKCELL program. This analysis states that the lattice intrinsic strainof the sample is so small and the crystal size is on the order of 559Å.
Abstract: Team distillation assisted by microwave extraction
(SDAM) considered as accelerated technique extraction is a
combination of microwave heating and steam distillation, performed
at atmospheric pressure. SDAM has been compared with the same
technique coupled with the cryogrinding of seeds (SDAM -CG).
Isolation and concentration of volatile compounds are performed by a
single stage for the extraction of essential oil from Cuminum
cyminum seeds. The essential oils extracted by these two methods for
5 min were quantitatively (yield) and qualitatively (aromatic profile)
no similar. These methods yield an essential oil with higher amounts
of more valuable oxygenated compounds, and allow substantial
savings of costs, in terms of time, energy and plant material. SDAM
and SDAM-CG is a green technology and appears as a good
alternative for the extraction of essential oils from aromatic plants.
Abstract: In this paper in consideration of each available
techniques deficiencies for speech recognition, an advanced method
is presented that-s able to classify speech signals with the high
accuracy (98%) at the minimum time. In the presented method, first,
the recorded signal is preprocessed that this section includes
denoising with Mels Frequency Cepstral Analysis and feature
extraction using discrete wavelet transform (DWT) coefficients; Then
these features are fed to Multilayer Perceptron (MLP) network for
classification. Finally, after training of neural network effective
features are selected with UTA algorithm.
Abstract: Hot Mix Asphalt (HMA) is one of the most
commonest constructed asphalts in Iran and the quality control of
constructed roads with HMA have been always paid due attention by
researchers. The quality control of constructed roads with this
method is being usually carried out by measuring volumetric
parameters of HMA marshall samples. One of the important
parameters that has a critical role in changing these volumetric
parameters is “compaction temperature"; which as a result of its
changing, volumetric parameters of Marshall Samples and
subsequently constructed asphalt is encountered with variations. In
this study, considering the necessity of preservation of the
compaction temperature, the effect of various temperatures on Hot
Mix Asphalt (HMA) samples properties has been evaluated. As well,
to evaluate the effect of this parameter on different grading, two
different grading (Top coat index grading and binder index grading)
have been used and samples were compacted at 5 various
temperatures.
Abstract: In this work a novel approach for color image
segmentation using higher order entropy as a textural feature for
determination of thresholds over a two dimensional image histogram
is discussed. A similar approach is applied to achieve multi-level
thresholding in both grayscale and color images. The paper discusses
two methods of color image segmentation using RGB space as the
standard processing space. The threshold for segmentation is decided
by the maximization of conditional entropy in the two dimensional
histogram of the color image separated into three grayscale images of
R, G and B. The features are first developed independently for the
three ( R, G, B ) spaces, and combined to get different color
component segmentation. By considering local maxima instead of the
maximum of conditional entropy yields multiple thresholds for the
same image which forms the basis for multilevel thresholding.
Abstract: This paper investigates experimental and numerical study of the airflow characteristics for vortex, round and square ceiling diffusers and its effect on the thermal comfort in a ventilated room. Three different thermal comfort criteria namely; Mean Age of the Air (MAA), ventilation effectiveness (E), and Effective Draft Temperature (EDT) have been used to predict the thermal comfort zone inside the room. In experimental work, a sub-scale room is set-up to measure the temperature field in the room. In numerical analysis, unstructured grids have been used to discretize the numerical domain. Conservation equations are solved using FLUENT commercial flow solver. The code is validated by comparing the numerical results obtained from three different turbulence models with the available experimental data. The comparison between the various numerical models shows that the standard k-ε turbulence model can be used to simulate these cases successfully. After validation of the code, effect of supply air velocity on the flow and thermal field could be investigated and hence the thermal comfort. The results show that the pressure coefficient created by the square diffuser is 1.5 times greater than that created by the vortex diffuser. The velocity decay coefficient is nearly the same for square and round diffusers and is 2.6 times greater than that for the vortex diffuser.
Abstract: In this paper we will develop further the sequential life test approach presented in a previous article by [1] using an underlying two parameter Inverse Weibull sampling distribution. The location parameter or minimum life will be considered equal to zero. Once again we will provide rules for making one of the three possible decisions as each observation becomes available; that is: accept the null hypothesis H0; reject the null hypothesis H0; or obtain additional information by making another observation. The product being analyzed is a new electronic component. There is little information available about the possible values the parameters of the corresponding Inverse Weibull underlying sampling distribution could have.To estimate the shape and the scale parameters of the underlying Inverse Weibull model we will use a maximum likelihood approach for censored failure data. A new example will further develop the proposed sequential life testing approach.
Abstract: Samples of CoFe2-xCrxO4 where x varies from 0.0 to 0.5 were prepared by co-precipitation route. These samples were sintered at 750°C for 2 hours. These particles were characterized by X-ray diffraction (XRD) at room temperature. The FCC spinel structure was confirmed by XRD patterns of the samples. The crystallite sizes of these particles were calculated from the most intense peak by Scherrer formula. The crystallite sizes lie in the range of 37-60 nm. The lattice parameter was found decreasing upon substitution of Cr. DC electrical resistivity was measured as a function of temperature. The room temperature thermoelectric power was measured for the prepared samples. The magnitude of Seebeck coefficient depends on the composition and resistivity of the samples.
Abstract: Recently, a growing interest has emerged on the
development of new and efficient energy sources, due to the inevitable extinction of the nonrenewable energy reserves. One of
these alternative sources which has a great potential and sustainability to meet up the energy demand is biomass energy. This
significant energy source can be utilized with various energy
conversion technologies, one of which is biomass gasification in
supercritical water.
Water, being the most important solvent in nature, has very important characteristics as a reaction solvent under supercritical
circumstances. At temperatures above its critical point (374.8oC and
22.1 MPa), water becomes more acidic and its diffusivity increases.
Working with water at high temperatures increases the thermal
reaction rate, which in consequence leads to a better dissolving of the
organic matters and a fast reaction with oxygen. Hence, supercritical water offers a control mechanism depending on solubility, excellent
transport properties based on its high diffusion ability and new reaction possibilities for hydrolysis or oxidation.
In this study the gasification of a real biomass, namely olive mill
wastewater (OMW), in supercritical water is investigated with the
use of Pt/Al2O3 and Ni/Al2O3 catalysts. OMW is a by-product
obtained during olive oil production, which has a complex nature
characterized by a high content of organic compounds and
polyphenols. These properties impose OMW a significant pollution
potential, but at the same time, the high content of organics makes
OMW a desirable biomass candidate for energy production.
All of the catalytic gasification experiments were made with five
different reaction temperatures (400, 450, 500, 550 and 600°C),
under a constant pressure of 25 MPa. For the experiments conducted
with Ni/Al2O3 catalyst, the effect of five reaction times (30, 60, 90,
120 and 150 s) was investigated. However, procuring that similar
gasification efficiencies could be obtained at shorter times, the experiments were made by using different reaction times (10, 15, 20,
25 and 30 s) for the case of Pt/Al2O3 catalyst. Through these experiments, the effects of temperature, time and catalyst type on the
gasification yields and treatment efficiencies were investigated.
Abstract: Due to the non- intuitive nature of Quantum
algorithms, it becomes difficult for a classically trained person to
efficiently construct new ones. So rather than designing new
algorithms manually, lately, Genetic algorithms (GA) are being
implemented for this purpose. GA is a technique to automatically
solve a problem using principles of Darwinian evolution. This has
been implemented to explore the possibility of evolving an n-qubit
circuit when the circuit matrix has been provided using a set of
single, two and three qubit gates. Using a variable length population
and universal stochastic selection procedure, a number of possible
solution circuits, with different number of gates can be obtained for
the same input matrix during different runs of GA. The given
algorithm has also been successfully implemented to obtain two and
three qubit Boolean circuits using Quantum gates. The results
demonstrate the effectiveness of the GA procedure even when the
search spaces are large.
Abstract: In this paper, we apply the FM methodology to the
cross-section of Romanian-listed common stocks and investigate the
explanatory power of market beta on the cross-section of commons
stock returns from Bucharest Stock Exchange. Various assumptions
are empirically tested, such us linearity, market efficiency, the “no
systematic effect of non-beta risk" hypothesis or the positive
expected risk-return trade-off hypothesis. We find that the Romanian
stock market shows the same properties as the other emerging
markets in terms of efficiency and significance of the linear riskreturn
models. Our analysis included weekly returns from January
2002 until May 2010 and the portfolio formation, estimation and
testing was performed in a rolling manner using 51 observations (one
year) for each stage of the analysis.
Abstract: The classic problem of recovering arbitrary values of
a band-limited signal from its samples has an added complication
in software radio applications; namely, the resampling calculations
inevitably fold aliases of the analog signal back into the original
bandwidth. The phenomenon is quantified by the spur-free dynamic
range. We demonstrate how a novel application of the Remez (Parks-
McClellan) algorithm permits optimal signal recovery and SFDR, far
surpassing state-of-the-art resamplers.