Abstract: Global Solar Radiation (H) for Dubai and Sharjah,
Latitude 25.25oN, Longitude 55oE and 25.29oN, Longitude 55oE
respectively have been studied using sunshine hour data (n) of the
areas using various methods. These calculated global solar radiation
values are then compared to the measured values presented by
NASA. Furthermore, the extraterrestrial (H0), diffuse (Hd) and beam
radiation (Hb) are also calculated. The diffuse radiation is calculated
using methods proposed by Page and Liu and Jordan (L-J). Diffuse
Radiation from the Page method is higher than the L-J method.
Moreover, the clearness index (KT) signifies a clear sky almost all
year round. Rainy days are hardly a few in a year and limited in the
months December to March. The temperature remains between 25oC
in winter to 44oC in summer and is desirable for thermal applications
of solar energy. From the estimated results, it appears that solar
radiation can be utilized very efficiently throughout the year for
photovoltaic and thermal applications.
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: Highly ordered arrays of TiO2 nanotubes (TiNTs) were grown vertically on Ti foil by electrochemical anodization. We controlled the lengths of these TiNTs from 2.4 to 26.8 ¶üÇóμm while varying the water contents (1, 3, and 6 wt%) of the electrolyte in ethylene glycol in the presence of 0.5 wt% NH4F with anodization for various applied voltages (20–80 V), periods (10–240 min) and temperatures (10–30 oC). For vertically aligned TiNT arrays, not only the increase in their tube lengths, but also their geometric (wall thickness and surface roughness) and crystalline structure lead to a significant influence on photocatalytic activity. The length optimization for methylene blue (MB) photodegradation was 18 μm. Further extending the TiNT length yielded lower photocatalytic activity presumably related to the limited MB diffusion and light-penetration depth into the TiNT arrays. The results indicated that a maximum MB photodegradation rate was obtained for the discrete anatase TiO2 nanotubes with thick and rough walls.
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: When the profile information of an existing road is
missing or not up-to-date and the parameters of the vertical
alignment are needed for engineering analysis, the engineer has to recreate
the geometric design features of the road alignment using
collected profile data. The profile data may be collected using
traditional surveying methods, global positioning systems, or digital
imagery. This paper develops a method that estimates the parameters
of the geometric features that best characterize the existing vertical
alignments in terms of tangents and the expressions of the curve, that
may be symmetrical, asymmetrical, reverse, and complex vertical
curves. The method is implemented using an Excel-based
optimization method that minimizes the differences between the
observed profile and the profiles estimated from the equations of the
vertical curve. The method uses a 'wireframe' representation of the
profile that makes the proposed method applicable to all types of
vertical curves. A secondary contribution of this paper is to introduce
the properties of the equal-arc asymmetrical curve that has been
recently developed in the highway geometric design field.
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: Biochemical Oxygen Demand (BOD) is a measure of
the oxygen used in bacteria mediated oxidation of organic substances
in water and wastewater. Theoretically an infinite time is required for
complete biochemical oxidation of organic matter, but the
measurement is made over 5-days at 20 0C or 3-days at 27 0C test
period with or without dilution. Researchers have worked to further
reduce the time of measurement.
The objective of this paper is to review advancement made in
BOD measurement primarily to minimize the time and negate the
measurement difficulties. Survey of literature review in four such
techniques namely BOD-BARTTM, Biosensors, Ferricyanidemediated
approach, luminous bacterial immobilized chip method.
Basic principle, method of determination, data validation and their
advantage and disadvantages have been incorporated of each of the
methods.
In the BOD-BARTTM method the time lag is calculated for the
system to change from oxidative to reductive state. BIOSENSORS
are the biological sensing element with a transducer which produces
a signal proportional to the analyte concentration. Microbial species
has its metabolic deficiencies. Co-immobilization of bacteria using
sol-gel biosensor increases the range of substrate. In ferricyanidemediated
approach, ferricyanide has been used as e-acceptor instead
of oxygen. In Luminous bacterial cells-immobilized chip method,
bacterial bioluminescence which is caused by lux genes was
observed. Physiological responses is measured and correlated to
BOD due to reduction or emission.
There is a scope to further probe into the rapid estimation of BOD.
Abstract: An adaptive Helmholtz resonator was designed and
adapted to hydraulics. The resonator was controlled by open- and
closed-loop controls so that 20 dB attenuation of the peak-to-peak
value of the pulsating pressure was maintained. The closed-loop
control was noted to be better, albeit it was slower because of its low
pressure and temperature variation, which caused variation in the
effective bulk modulus of the hydraulic system. Low-pressure
hydraulics contains air, which affects the stiffness of the hydraulics,
and temperature variation changes the viscosity of the oil. Thus, an
open-loop control loses its efficiency if a condition such as
temperature or the amount of air changes after calibration. The
instability of the low-pressure hydraulic system reduced the
operational frequency range of the Helmholtz resonator when
compared with the results of an analytical model.
Different dampers for hydraulics are presented. Then analytical
models of a hydraulic pipe and a hydraulic pipe with a Helmholtz
resonator are presented. The analytical models are based on the wave
equation of sound pressure. Finally, control methods and the results
of experiments are presented.
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.
Abstract: An efficient parallel form in digital signal processor can improve the algorithm performance. The butterfly structure is an important role in fast Fourier transform (FFT), because its symmetry form is suitable for hardware implementation. Although it can perform a symmetric structure, the performance will be reduced under the data-dependent flow characteristic. Even though recent research which call as novel memory reference reduction methods (NMRRM) for FFT focus on reduce memory reference in twiddle factor, the data-dependent property still exists. In this paper, we propose a parallel-computing approach for FFT implementation on digital signal processor (DSP) which is based on data-independent property and still hold the property of low-memory reference. The proposed method combines final two steps in NMRRM FFT to perform a novel data-independent structure, besides it is very suitable for multi-operation-unit digital signal processor and dual-core system. We have applied the proposed method of radix-2 FFT algorithm in low memory reference on TI TMSC320C64x DSP. Experimental results show the method can reduce 33.8% clock cycles comparing with the NMRRM FFT implementation and keep the low-memory reference property.
Abstract: Sorghum flour was supplemented with 15 and 30%
chickpea flour. Sorghum flour and the supplement were fermented at
35 oC for 0, 8, 16, and 24 h. Changes in pH, titrable acidity, total
soluble solids, protein content, in vitro protein digestibility and
amino acid composition were investigated during fermentation and/or
after supplementation of sorghum flour with chickpea. The pH of the
fermenting material decreased sharply with a concomitant increase in
the titrable acidity. The total soluble solids remained unchanged with
progressive fermentation time. The protein content of sorghum
cultivar was found to be 9.27 and that of chickpea was 22.47%. The
protein content of sorghum cultivar after supplementation with15 and
30% chickpea was significantly (P ≤ 0.05) increased to 11.78 and
14.55%, respectively. The protein digestibility also increased after
fermentation from 13.35 to 30.59 and 40.56% for the supplements,
respectively. Further increment in protein content and digestibility
was observed when supplemented and unsupplemented samples were
fermented for different periods of time. Cooking of fermented
samples was found to increase the protein content slightly and
decreased digestibility for both supplements. Amino acid content of
fermented and fermented and cooked supplements was determined.
Supplementation was found to increase the lysine and therionine
content. Cooking following fermentation decreased lysine,
isoleucine, valine and sulfur containg amino acids.
Abstract: Pressure driven microscale gas flow-separation has
been investigated by solving the compressible Navier-Stokes (NS)
system of equations. A two dimensional explicit finite volume (FV)
compressible flow solver has been developed using modified
advection upwind splitting methods (AUSM+) with no-slip/first
order Maxwell-s velocity slip conditions to predict the flowseparation
behavior in microdimensions. The effects of scale-factor
of the flow geometry and gas species on the microscale gas flowseparation
have been studied in this work. The intensity of flowseparation
gets reduced with the decrease in scale of the flow
geometry. In reduced dimension, flow-separation may not at all be
present under similar flow conditions compared to the larger flow
geometry. The flow-separation patterns greatly depend on the
properties of the medium under similar flow conditions.
Abstract: When programming in languages such as C, Java, etc.,
it is difficult to reconstruct the programmer's ideas only from the
program code. This occurs mainly because, much of the programmer's
ideas behind the implementation are not recorded in the code during
implementation. For example, physical aspects of computation such as
spatial structures, activities, and meaning of variables are not required
as instructions to the computer and are often excluded. This makes the
future reconstruction of the original ideas difficult. AIDA, which is a
multimedia programming language based on the cyberFilm model, can
solve these problems allowing to describe ideas behind programs
using advanced annotation methods as a natural extension to
programming. In this paper, a development environment that
implements the AIDA language is presented with a focus on the
annotation methods. In particular, an actual scientific numerical
computation code is created and the effects of the annotation methods
are analyzed.
Abstract: Knowledge discovery from text and ontology learning
are relatively new fields. However their usage is extended in many
fields like Information Retrieval (IR) and its related domains. Human
Plausible Reasoning based (HPR) IR systems for example need a
knowledge base as their underlying system which is currently made
by hand. In this paper we propose an architecture based on ontology
learning methods to automatically generate the needed HPR
knowledge base.
Abstract: A new stochastic algorithm called Probabilistic Global Search Johor (PGSJ) has recently been established for global optimization of nonconvex real valued problems on finite dimensional Euclidean space. In this paper we present convergence guarantee for this algorithm in probabilistic sense without imposing any more condition. Then, we jointly utilize this algorithm along with control
parameterization technique for the solution of constrained optimal control problem. The numerical simulations are also included to illustrate the efficiency and effectiveness of the PGSJ algorithm in the solution of control problems.
Abstract: Sparse representation has long been studied and several
dictionary learning methods have been proposed. The dictionary
learning methods are widely used because they are adaptive. In this
paper, a new dictionary learning method for audio is proposed. Signals
are at first decomposed into different degrees of Intrinsic Mode
Functions (IMF) using Empirical Mode Decomposition (EMD)
technique. Then these IMFs form a learned dictionary. To reduce the
size of the dictionary, the K-means method is applied to the dictionary
to generate a K-EMD dictionary. Compared to K-SVD algorithm, the
K-EMD dictionary decomposes audio signals into structured
components, thus the sparsity of the representation is increased by
34.4% and the SNR of the recovered audio signals is increased by
20.9%.
Abstract: Preprocessing of speech signals is considered a crucial step in the development of a robust and efficient speech or speaker recognition system. In this paper, we present some popular statistical outlier-detection based strategies to segregate the silence/unvoiced part of the speech signal from the voiced portion. The proposed methods are based on the utilization of the 3 σ edit rule, and the Hampel Identifier which are compared with the conventional techniques: (i) short-time energy (STE) based methods, and (ii) distribution based methods. The results obtained after applying the proposed strategies on some test voice signals are encouraging.
Abstract: Non-Destructive evaluation of in-service power
transformer condition is necessary for avoiding catastrophic failures.
Dissolved Gas Analysis (DGA) is one of the important methods.
Traditional, statistical and intelligent DGA approaches have been
adopted for accurate classification of incipient fault sources.
Unfortunately, there are not often enough faulty patterns required for
sufficient training of intelligent systems. By bootstrapping the
shortcoming is expected to be alleviated and algorithms with better
classification success rates to be obtained. In this paper the
performance of an artificial neural network, K-Nearest Neighbour
and support vector machine methods using bootstrapped data are
detailed and shown that while the success rate of the ANN algorithms
improves remarkably, the outcome of the others do not benefit so
much from the provided enlarged data space. For assessment, two
databases are employed: IEC TC10 and a dataset collected from
reported data in papers. High average test success rate well exhibits
the remarkable outcome.
Abstract: Many measures have been proposed for machine
translation evaluation (MTE) while little research has been done on
the performance of MTE methods. This paper is an effort for MTE
performance analysis. A general frame is proposed for the description
of the MTE measure and the test suite, including whether the
automatic measure is consistent with human evaluation, whether
different results from various measures or test suites are consistent,
whether the content of the test suite is suitable for performance
evaluation, the degree of difficulty of the test suite and its influence
on the MTE, the relationship of MTE result significance and the size
of the test suite, etc. For a better clarification of the frame, several
experiment results are analyzed relating human evaluation, BLEU
evaluation, and typological MTE. A visualization method is
introduced for better presentation of the results. The study aims for
aid in construction of test suite and method selection in MTE
practice.
Abstract: This paper considers a multi criteria cell formation
problem in Cellular Manufacturing System (CMS). Minimizing the
number of voids and exceptional elements in cells simultaneously are
two proposed objective functions. This problem is an Np-hard
problem according to the literature, and therefore, we can-t find the
optimal solution by an exact method. In this paper we developed two
ant algorithms, Ant Colony Optimization (ACO) and Max-Min Ant
System (MMAS), based on Data Envelopment Analysis (DEA). Both
of them try to find the efficient solutions based on efficiency concept
in DEA. Each artificial ant is considered as a Decision Making Unit
(DMU). For each DMU we considered two inputs, the values of
objective functions, and one output, the value of one for all of them.
In order to evaluate performance of proposed methods we provided
an experimental design with some empirical problem in three
different sizes, small, medium and large. We defined three different
criteria that show which algorithm has the best performance.