Abstract: The tubes in an Ammonia primary reformer furnace
operate close to the limits of materials technology in terms of the
stress induced as a result of very high temperatures, combined with
large differential pressures across the tube wall. Operation at tube
wall temperatures significantly above design can result in a rapid
increase in the number of tube failures, since tube life is very
sensitive to the absolute operating temperature of the tube. Clearly it
is important to measure tube wall temperatures accurately in order to
prevent premature tube failure by overheating.. In the present study,
the catalyst tubes in an Ammonia primary reformer has been modeled
taking into consideration heat, mass and momentum transfer as well
as reformer characteristics.. The investigations concern the effects of
tube characteristics and superficial tube wall temperatures on of the
percentage of heat flux, unconverted methane and production of
Hydrogen for various values of steam to carbon ratios. The results
show the impact of catalyst tubes length and diameters on the
performance of operating parameters in ammonia primary reformers.
Abstract: This paper discusses the approach of real-time
controlling of the energy management system using the data
acquisition tool of LabVIEW. The main idea of this inspiration was
to interface the Station (PC) with the system and publish the data on
internet using LabVIEW. In this venture, controlling and switching of
3 phase AC loads are effectively and efficiently done. The phases are
also sensed through devices. In case of any failure the attached
generator starts functioning automatically. The computer sends
command to the system and system respond to the request. The
modern feature is to access and control the system world-wide using
world wide web (internet). This controlling can be done at any time
from anywhere to effectively use the energy especially in developing
countries where energy management is a big problem. In this system
totally integrated devices are used to operate via remote location.
Abstract: This paper describes a newly designed decentralized
nonlinear control strategy to control a robot manipulator. Based on the
concept of the nonlinear state feedback theory and decentralized
concept is developed to improve the drawbacks in previous works
concerned with complicate intelligent control and low cost effective
sensor. The control methodology is derived in the sense of Lyapunov
theorem so that the stability of the control system is guaranteed. The
decentralized algorithm does not require other joint angle and velocity
information. Individual Joint controller is implemented using a digital
processor with nearly actuator to make it possible to achieve good
dynamics and modular. Computer simulation result has been
conducted to validate the effectiveness of the proposed control scheme
under the occurrence of possible uncertainties and different reference
trajectories. The merit of the proposed control system is indicated in
comparison with a classical control system.
Abstract: Dill (Anethum graveolens L.) is a popular herb used in
many regions, including Baltic countries. Dill is widely used for
flavoring foods and beverages due to its pleasant spicy aroma. The
aim of this work was to determine the best blanching method for
processing of dill prior to microwave vacuum drying based on
sensory properties, color and volatile compounds in dried product.
Two blanching mediums were used – water and steam, and for part of
samples microwave pretreatment was additionally used. Evaluation of
dried dill volatile aroma compounds, color changes and sensory
attributes was performed. Results showed that blanching significantly
influences the quality of dried dill. After evaluation of volatile aroma
compounds, color and sensory properties of microwave vacuum dried
dill, as the best method for dill pretreatment was established
blanching at 90 °C for 30 s.
Abstract: This paper presents a new and efficient approach for
capacitor placement in radial distribution systems that determine
the optimal locations and size of capacitor with an objective of
improving the voltage profile and reduction of power loss. The
solution methodology has two parts: in part one the loss sensitivity
factors are used to select the candidate locations for the capacitor
placement and in part two a new algorithm that employs Plant growth
Simulation Algorithm (PGSA) is used to estimate the optimal size
of capacitors at the optimal buses determined in part one. The main
advantage of the proposed method is that it does not require any
external control parameters. The other advantage is that it handles the
objective function and the constraints separately, avoiding the trouble
to determine the barrier factors. The proposed method is applied to 9
and 34 bus radial distribution systems. The solutions obtained by the
proposed method are compared with other methods. The proposed
method has outperformed the other methods in terms of the quality
of solution.
Abstract: Diagnostic and detection of the arterial stiffness is
very important; which gives indication of the associated increased risk of cardiovascular diseases. To make a cheap and easy method for general screening technique to avoid the future cardiovascular
complexes , due to the rising of the arterial stiffness ; a proposed algorithm depending on photoplethysmogram to be used. The
photoplethysmograph signals would be processed in MATLAB. The
signal will be filtered, baseline wandering removed, peaks and
valleys detected and normalization of the signals should be achieved
.The area under the catacrotic phase of the photoplethysmogram
pulse curve is calculated using trapezoidal algorithm ; then will used
in cooperation with other parameters such as age, height, blood
pressure in neural network for arterial stiffness detection. The Neural
network were implemented with sensitivity of 80%, accuracy 85%
and specificity of 90% were got from the patients data. It is
concluded that neural network can detect the arterial STIFFNESS
depending on risk factor parameters.
Abstract: The determination of sugars in foods is very
significant. Their relation in fact, can affect the chemical and
sensorial quality of the matrix (e.g., sweetness, pH, total acidity,
microbial stability, global acceptability) and can provide information
on food to optimize several selected technological processes. Three
stages of ripeness (green, yellow and red) of tomatoes (Lycopersicon
Esculentum cv. Elegance) at different harvest dates were evaluated.
Fruit from all harvests were exposed to different of ozone doses
(0.25, 0.50 and 1 mg O3/g tomatoes) and clean air for 5 day at 15
°C±2 and 90-95 % relative humidity. Then, fruits were submitted for
extraction and analysis after a day from the finish of exposure of each
stage. The concentrations of the glucose and fructose increased in the
tomatoes which were subjected to ozone treatments.
Abstract: Global approximation using metamodel for complex
mathematical function or computer model over a large variable
domain is often needed in sensibility analysis, computer simulation,
optimal control, and global design optimization of complex, multiphysics
systems. To overcome the limitations of the existing
response surface (RS), surrogate or metamodel modeling methods for
complex models over large variable domain, a new adaptive and
regressive RS modeling method using quadratic functions and local
area model improvement schemes is introduced. The method applies
an iterative and Latin hypercube sampling based RS update process,
divides the entire domain of design variables into multiple cells,
identifies rougher cells with large modeling error, and further divides
these cells along the roughest dimension direction. A small number
of additional sampling points from the original, expensive model are
added over the small and isolated rough cells to improve the RS
model locally until the model accuracy criteria are satisfied. The
method then combines local RS cells to regenerate the global RS
model with satisfactory accuracy. An effective RS cells sorting
algorithm is also introduced to improve the efficiency of model
evaluation. Benchmark tests are presented and use of the new
metamodeling method to replace complex hybrid electrical vehicle
powertrain performance model in vehicle design optimization and
optimal control are discussed.
Abstract: This paper summarizes the results of some experiments for finding the effective features for disambiguation of Turkish verbs. Word sense disambiguation is a current area of investigation in which verbs have the dominant role. Generally verbs have more senses than the other types of words in the average and detecting these features for verbs may lead to some improvements for other word types. In this paper we have considered only the syntactical features that can be obtained from the corpus and tested by using some famous machine learning algorithms.
Abstract: This paper proposes a new technique to detect code
clones from the lexical and syntactic point of view, which is based
on PALEX source code representation. The PALEX code contains
the recorded parsing actions and also lexical formatting information
including white spaces and comments. We can record a list of parsing
actions (shift, reduce, and reading a token) during a compiling process
after a compiler finishes analyzing the source code. The proposed
technique has advantages for syntax sensitive approach and language
independency.
Abstract: This paper study the high-level modelling and design
of delta-sigma (ΔΣ) noise shapers for audio Digital-to-Analog
Converter (DAC) so as to eliminate the in-band Signal-to-Noise-
Ratio (SNR) degradation that accompany one channel mismatch in
audio signal. The converter combines a cascaded digital signal
interpolation, a noise-shaping single loop delta-sigma modulator with
a 5-bit quantizer resolution in the final stage. To reduce sensitivity of
Digital-to-Analog Converter (DAC) nonlinearities of the last stage, a
high pass second order Data Weighted Averaging (R2DWA) is
introduced. This paper presents a MATLAB description modelling
approach of the proposed DAC architecture with low distortion and
swing suppression integrator designs. The ΔΣ Modulator design can
be configured as a 3rd-order and allows 24-bit PCM at sampling rate
of 64 kHz for Digital Video Disc (DVD) audio application. The
modeling approach provides 139.38 dB of dynamic range for a 32
kHz signal band at -1.6 dBFS input signal level.
Abstract: A biosensor based on glucose oxidase (GOx) immobilized onto nanoparticles zirconium oxide with polyethylene nanocomposite for glucose monitoring has been designed. The CTAB/PEG/ZrO2/GOx nanocomposite was deposited onto screen printed carbon paste (SPCE) electrode via spin coating technique. The properties of CTAB/PEG/ZrO2/GOx were study using scanning electron microscopy (SEM). The SPE modified with the CTAB/PEG/ZrO2/GOx showed electrocatalytical response to the oxidation of glucose when ferrocene carboxaldehyde was used as an artificial redox mediator, which was studied by cyclic voltammetry (CV). Several parameters such as working potential, effect of pH and effect of ZrO2/PEG layers that governed the analytical performance of the biosensor, have been studied. The biosensor was applied to detect glucose with a linear range of 0.4 to 2.0 mmol L−1 with good repetability and reproducibility.
Abstract: Vinegar or sour wine is a product of alcoholic and
subsequent acetous fermentation of sugary precursors derived from
several fruits or starchy substrates. This delicious food additive and
supplement contains not less than 4 grams of acetic acid in 100 cubic
centimeters at 20°C. Among the large number of bacteria that are
able to produce acetic acid, only few genera are used in vinegar
industry most significant of which are Acetobacter and
Gluconobacter. In this research we isolated and identified an
Acetobacter strain from Iranian apricot, a very delicious and sensitive
summer fruit to decay, we gathered from fruit's stores in Isfahan,
Iran. The main culture media we used were Carr, GYC, Frateur and
an industrial medium for vinegar production. We isolated this strain
using a novel miniature fermentor we made at Pars Yeema
Biotechnologists Co., Isfahan Science and Technology Town (ISTT),
Isfahan, Iran. The microscopic examinations of isolated strain from
Iranian apricot showed gram negative rods to cocobacilli. Their
catalase reaction was positive and oxidase reaction was negative and
could ferment ethanol to acetic acid. Also it showed an acceptable
growth in 5%, 7% and 9% ethanol concentrations at 30°C using
modified Carr media after 24, 48 and 96 hours incubation
respectively. According to its tolerance against high concentrations of
ethanol after four days incubation and its high acetic acid production,
8.53%, after 144 hours, this strain could be considered as a suitable
industrial strain for a production of a new type of vinegar, apricot
vinegar, with a new and delicious taste. In conclusion this is the first
report of isolation and identification of an Acetobacter strain from
Iranian apricot with a very good tolerance against high ethanol
concentrations as well as high acetic acid productivity in an
acceptable incubation period of time industrially. This strain could be
used in vinegar industry to convert apricot spoilage to a beneficiary
product and mentioned characteristics have made it as an amenable
strain in food and agricultural biotechnology.
Abstract: Interactive installations for public spaces are a
particular kind of interactive systems, the design of which has been
the subject of several research studies. Sensor-based applications are
becoming increasingly popular, but the human-computer interaction
community is still far from reaching sound, effective large-scale
interactive installations for public spaces. The 6DSpaces project is
described in this paper as a research approach based on studying the
role of multisensory interactivity and how it can be effectively used
to approach people to digital, scientific contents. The design of an
entire scientific exhibition is described and the result was evaluated
in the real world context of a Science Centre. Conclusions bring
insight into how the human-computer interaction should be designed
in order to maximize the overall experience.
Abstract: Signal processing applications which are iterative in
nature are best represented by data flow graphs (DFG). In these
applications, the maximum sampling frequency is dependent on the
topology of the DFG, the cyclic dependencies in particular. The
determination of the iteration bound, which is the reciprocal of the
maximum sampling frequency, is critical in the process of hardware
implementation of signal processing applications. In this paper, a
novel technique to compute the iteration bound is proposed. This
technique is different from all previously proposed techniques, in the
sense that it is based on the natural flow of tokens into the DFG
rather than the topology of the graph. The proposed algorithm has
lower run-time complexity than all known algorithms. The
performance of the proposed algorithm is illustrated through
analytical analysis of the time complexity, as well as through
simulation of some benchmark problems.
Abstract: This paper addresses the problem of how one can
improve the performance of a non-optimal filter. First the theoretical question on dynamical representation for a given time correlated
random process is studied. It will be demonstrated that for a wide class of random processes, having a canonical form, there exists
a dynamical system equivalent in the sense that its output has the
same covariance function. It is shown that the dynamical approach is more effective for simulating and estimating a Markov and non-
Markovian random processes, computationally is less demanding,
especially with increasing of the dimension of simulated processes.
Numerical examples and estimation problems in low dimensional
systems are given to illustrate the advantages of the approach. A very useful application of the proposed approach is shown for the
problem of state estimation in very high dimensional systems. Here a modified filter for data assimilation in an oceanic numerical model
is presented which is proved to be very efficient due to introducing
a simple Markovian structure for the output prediction error process
and adaptive tuning some parameters of the Markov equation.
Abstract: In this work, propagation of uncertainty during calibration
process of TRANUS, an integrated land use and transport model
(ILUTM), has been investigated. It has also been examined, through a
sensitivity analysis, which input parameters affect the variation of the
outputs the most. Moreover, a probabilistic verification methodology
of calibration process, which equates the observed and calculated
production, has been proposed. The model chosen as an application is
the model of the city of Grenoble, France. For sensitivity analysis and
uncertainty propagation, Monte Carlo method was employed, and a
statistical hypothesis test was used for verification. The parameters of
the induced demand function in TRANUS, were assumed as uncertain
in the present case. It was found that, if during calibration, TRANUS
converges, then with a high probability the calibration process is
verified. Moreover, a weak correlation was found between the inputs
and the outputs of the calibration process. The total effect of the
inputs on outputs was investigated, and the output variation was found
to be dictated by only a few input parameters.
Abstract: Embedding and extraction of a secret information as
well as the restoration of the original un-watermarked image is
highly desirable in sensitive applications like military, medical, and
law enforcement imaging. This paper presents a novel reversible
data-hiding method for digital images using integer to integer
wavelet transform and companding technique which can embed and
recover the secret information as well as can restore the image to its
pristine state. The novel method takes advantage of block based
watermarking and iterative optimization of threshold for companding
which avoids histogram pre and post-processing. Consequently, it
reduces the associated overhead usually required in most of the
reversible watermarking techniques. As a result, it keeps the
distortion small between the marked and the original images.
Experimental results show that the proposed method outperforms the
existing reversible data hiding schemes reported in the literature.
Abstract: Given a large sparse signal, great wishes are to
reconstruct the signal precisely and accurately from lease number of
measurements as possible as it could. Although this seems possible
by theory, the difficulty is in built an algorithm to perform the
accuracy and efficiency of reconstructing. This paper proposes a new
proved method to reconstruct sparse signal depend on using new
method called Least Support Matching Pursuit (LS-OMP) merge it
with the theory of Partial Knowing Support (PSK) given new method
called Partially Knowing of Least Support Orthogonal Matching
Pursuit (PKLS-OMP).
The new methods depend on the greedy algorithm to compute the
support which depends on the number of iterations. So to make it
faster, the PKLS-OMP adds the idea of partial knowing support of its
algorithm. It shows the efficiency, simplicity, and accuracy to get
back the original signal if the sampling matrix satisfies the Restricted
Isometry Property (RIP).
Simulation results also show that it outperforms many algorithms
especially for compressible signals.
Abstract: Due to the limited energy resources, energy efficient operation of sensor node is a key issue in wireless sensor networks. Clustering is an effective method to prolong the lifetime of energy constrained wireless sensor network. However, clustering in wireless sensor network faces several challenges such as selection of an optimal group of sensor nodes as cluster, optimum selection of cluster head, energy balanced optimal strategy for rotating the role of cluster head in a cluster, maintaining intra and inter cluster connectivity and optimal data routing in the network. In this paper, we propose a protocol supporting an energy efficient clustering, cluster head selection/rotation and data routing method to prolong the lifetime of sensor network. Simulation results demonstrate that the proposed protocol prolongs network lifetime due to the use of efficient clustering, cluster head selection/rotation and data routing.